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date: 27 February 2020

(p. 860) Subject Index

(p. 860) Subject Index

actions:
and mechanism‐based explanation 323, 325–9
dissonance‐driven desire formation 328
‘Old Regime’ pattern 328–9
rational imitation 328
self‐fulfilling prophecy 328
sour‐grapes syndrome 326
vacancy chains 328
wishful thinking 326
and social science explanation 322–3
actors:
and mechanisms 323
and social science explanation 322–3
AFDC benefits, and spatio‐temporal model 595–7
age, period, cohort (APC) models 325
agency, and causality 239–41
agent‐based modeling:
and agent interactions 84–6
and comparison with mathematical modeling 89–91
and complexity 91
and computational methods 78–9
and differences from game‐theoretic models 82–4
and elections:
agents as rule‐based objects 81–2
candidate behavior 80–1
following rules vs maximizing utility 82–4
and empirical testing 89, 90
and insights into social processes 90
and institutional design 90–1
and nature of 78–9
and potential of 79, 91
and quantitative research 331
and rise in causal thinking 6
and risks of 79
and social forms 84–6
and social outcomes 330
and system behavior 87–8
and theoretical focus of 330
aggregation:
and construction/evaluation of concepts and measures 98–103
homogeneity question 110
and time‐series models 469
Agreement, Method of 284
agreement theories 41
AIDS 312
Akaike's information criterion (AIC) 535
alliance dependence 714
American Journal of Political Science 339, 790, 809, 830
Work shop 817, 824
American National Elections Studies (ANES) 386, 388
and feeling thermometers 205–20
and political efficacy 449
and response rate 391
American Political Science Association 783
and Political Methodology Section 28, 796, 797, 811–12
and Qualitative and Multi‐Method Research Section 29, 784–6
and Task Force on Graduate Education 784
American Political Science Review 339, 476, 783, 790, 815, 817
and causal inference 4
American Psychological Association, and construct validity 122
The American Voter 798, 799–800, 814
Ann Arbor, and Summer Program 800, 801–2
continuing demand for 805–8
curriculum 804–5
Annual Review of Political Science 790
anomalies 313
Arizona State University 789
aspirin 292–3
attributes, and agent‐based modeling 81
attrition:
and experiments 16
and field experiments 372–3
audio computer‐assisted self‐interviewing (T‐ACASI) 386, 395
Australian Election Studies 386
autocorrelation 20
functions (ACF) 459
and multilevel models 607
autoregressive conditionally heteroskedastic (ARCH) model 464–5
autoregressive integrated moving average (ARIMA) 17, 459
and time‐series models 463–5
(p. 861) autoregressive moving average (ARMA), and time‐series models 463–5
average treatment effect (ATE) 362–3
average treatment effect among the treated (ATT) 275–6, 362–3
balance, and experiments 375–6
bargaining theory:
and Baron‐Ferejohn bargaining 76–8
and computational models 76–8
noncooperative 72
Baron‐Ferejohn bargaining, and computational models 76–8
baseline hazard, and survival analysis 531
Cox models' treatment of 534–6
Bayes' factors 505
Bayesian analysis 494, 508–9
and affirmation of hypotheses 711
and approach to statistical inference 495–7
and common concerns about 506–7
and elimination of hypotheses 711
and end of cold war 715–18
and epistemology 58–9
and generalized latent variable modeling 138
and generalizing from one/few cases 713–14
and limitations of 712–13, 719
and model fitting via simulation 497–501
Gibbs sampling algorithm 498–9
Metropolis‐Hastings algorithm 499–500
and multilevel models 614–15
and nature of evidence 710–12
and posterior distributions 21, 496, 497–501
Monte Carlo method 497–501
and practical advantages of 501
fitting otherwise intractable models 504–5
incorporation of prior information 504
intuitive interpretation of findings 502–3
missing data 506
model comparison 505–6
quantities of interest 503–4
and probabilities 503
and process tracing 702, 718–19
differences between 708, 714
similarities 708, 719
and software for 507–8
and theory testing 708–9
and underdetermination thesis 712–13
and uses of 702
Bayesian Information Criterion 506
bayesm (software package) 508
Bayes’s Theorem 496, 709, 713
behavioral revolution 52
and measurement of 7–12
and rise in causal thinking 6
behavioralism 687
and science 52
and traditions of political science 52
beliefs:
and individual actions 326
and meaning holism 62
benchmarking 282–3
beriberi 306–8
bias:
and case selection 675
and interviews 695
and measurement error 127
and measurement validity 121
and Neyman‐Rubin‐Holland (NRH) theory 275
and publication bias 377
binary dependent variables, and time‐series cross‐sectional (TSCS) methods 486–7
event history approaches 487–9
Markov transition models 490
Biometrika 199, 200
bounds, and ecological inference 552–3
Box‐Jenkins approach, and time‐series models 463
Box‐Taio intervention model 464
British Election Studies 399
BUGS language 507–8, 615
calibration 175–7, 197
and context‐setting conditions 176
and fuzzy‐set analysis 174, 175, 183
transforming interval‐scale variables 184–6
and measurement 9, 174
and populations 176
and scope conditions 176
and set theory 174
and statistical interaction 176–7
and techniques of 184
direct method 186–90
indirect method 190–3
and use of calibrated measures 193–6 see also measurement
Cal‐Learn experiment 264–5, 274
campaign expenditure 406
Canadian Election Studies 386, 399
cancer 218, 293
capacities 13
and causality 243
capitalism, and rise of 6
case selection 24–5
and ambiguities in selection strategies 677–8
changing status of case 677
mixing strategies 677
nature of research 677–8
and broader population 647
and case analysis 679
and crucial cases 659–63
confirmation of theory 659–61
degree of crucialness 663
(p. 862)
disconfirming of theory 659, 662–3
least‐likely 659–61, 662
most‐likely 659
theories amenable to 660–1
and deviant cases 655–6
relative nature of 655–6
theoretical anomalies 655
unrepresentativeness 656
uses of 656
and diverse cases 650–2
advantages of 652
identifying diversity 650–1
maximum variance 650
multiple variables 651
representativeness 652
typicality 652
typological theorizing 651
and extreme cases 653–4
definition 653
maximizing variance 654
methodological value 653
representativeness 654
and influential cases 656–9
aims of 656–7, 658
focus on outliers 657
sample size 658–9
and methods of 645–6
and most‐different cases 671–5
causal uniqueness 674
in combination with other approaches 673
defining element of 673–4
dichotomous variables 673
eliminating necessary causes 673–4
strength of 672
as supplemental method 674–5
and most‐similar cases 668–70
case control 669–70
caveats to 669
exploratory studies 668
hypothesis testing 668
identification of 670
matching techniques 670
nonrepresentativeness 670
purposes of 668
and multimethod research 758
random selection 758
and narrative choice:
convenience samples 762
‘good cases’ 761–2
random selection 758, 764–6
selection bias 761
structuring the narrative 766–8
variation in the dependent or independent variables 762–4
and narratives 757–8
and objectives of 678–9
and pathway cases 664–8
causal mechanisms 664, 666
causal sufficiency 664
continuous variables 666–7
exceptions 667–8
general‐purpose model 664–6
and pragmatic/logistical issues 679
and quantitative analysis 647
and representativeness 675–7
and sample bias 675–6
and theoretical prominence 679
and typical cases 648–50
causal typicality 649–50
inductive approach 648–9
probability of representativeness 650
uses of 650
case studies 26–7, 645
and causal inference 23, 773
and clinical medicine 293
and counterfactuals 628–9, 631
and degrees of freedom critique 711
and historical institutionalism 53
and identifying patterns 756
idiographic 631
and matching methods 281–3
and Mill’s methods 283–4, 288
conditions 282
Indirect Method of Difference 287–8
Method of Agreement 284
Method of Difference 284–7, 290
and qualitative comparative analysis 734
and types of 646, 647–8
and uses of 702 see also case selection; narratives
categorical variables, and typologies 156–7
categorization 8
causal complexity, and qualitative comparative analysis 725–6
causal process observations (CPOs) 14, 30
and scientific enquiry 301, 312–13
Eijkman and beriberi 306–8
Fleming and penicillin 310–11
Goldberger and pellagra 308–9
Gregg and German measles 311
Herbst and AIDS 312
Jenner and vaccination 301–2
literature 313–16
McKay and fluoridation 309–10
Semmelweis and puerperal fever 302–4
Snow and cholera 304–6
causality 3, 362–5
and agency 239
and approaches to 12–15, 218–19, 246–7
empirical research 247–9
(p. 863)
and asymmetric aspects of 246, 247
and capacities 243
and counterfactuals 13, 220–1, 232–3, 290, 629
closest possible worlds 234, 236–7
common causes 238
controlled experiments 236–7
evaluating counterfactual statements 234
Lewis's approach 233–5
pre‐emption 241–2
problems with definition of causation 237–8
temporal precedence 238
virtue of definition of causation 235–6
and determinism 225
and empirical research 247–9
and epistemological questions 225–6
and experiments 15–16, 247–9, 351
and human agency 239–41
and human dependence on 217
and Humean/neo‐Humean approaches 221–2, 226, 231–2
accidental regularities 229
asymmetry of causation 230–1
common causes 229–30
definition of cause 227
INUS conditions 227–9, 230–1
lawlike statements 230
and linguistic analysis of 223–4
and manipulation 223, 239–41
and meaning of 223
and mechanisms 243–5, 246–7, 320
multiple causes 246
and methodology 4
and Mill's methods 282, 283–4, 288
conditions 282
Indirect Method of Difference 287–8
Method of Agreement 284
Method of Difference 284–7, 290
and Neyman‐Rubin model 13
and ontological questions 224–5
and pairing problem 242–3
and philosophical questions about 217–18
and political science 4–5
and pre‐emption 241–2
and probabilism 225, 289
and psychological analysis of 221–3
and qualitative tools 23–6
and quantitative tools:
general methods 16–21
special topics 21–3
and reasons as causes 65–6
as regularity 221–2, 223
and requirements of strong inferences 218
and rise in causal thinking 4–5, 30
agent‐based model of 6
behavioral revolution 6
counterfactual approach 13, 23–4
experiments 16
invention of new tools 6
measurement of 7–12
qualitative approaches 24–6
regression analysis 12–13, 14–15, 17–19
self‐interest 5
social theory's perspective on 5–6
time‐series regressions 20
value change 6
in social research 12–15
and statistical inference 320
and statistical theory of 241
and surveys 396–7
and symmetric aspects of 246–7
and time‐series regressions 19–20 see also Neyman‐Rubin‐Holland (NRH) theory
centipede game 83
Centro de Investigación y Docencia Económicas (CIDE) 789
change:
and time‐series 456
and typologies 163–5
cholera 304–6
civil war onset:
and causes of 758–9
and incompleteness of statistical models 768–70
and narratives 773–4
learning from 770–3
random selection 765–6
structuring 766–8
and statistical analysis of 759–60
CLARIFY 522
classificatory types, and typologies 161–2
clinical medicine, see medicine
closest possible worlds, and counterfactuals 234, 236–7
Cochrane‐Orcutt 479
coercion 42
and interdependence 572
cold war, and end of 715–18
collective action, and self‐interest 37
Columbia University election studies 798–9
commitment, ontological 61–2
common shocks, and interdependence 575
comparative analysis:
and Bayesian approach 505–6
and typologies 168
comparative judgment, law of 201
Comparative Political Studies 790
Comparative Politics 790
comparative research:
and correlations 724, 725
and necessary conditions 724
(p. 864)
and set theory 724
and shared conditions 724
and shared outcomes 723–4
and specific connections 724–5
and sufficient conditions 724 see also qualitative comparative analysis (QCA)
comparative‐historical analysis 26
and conception of causation 747–8
and criticisms of 738
and definition of 739
and growth of scholarship 737–8
as leading research tradition 741
and literature of 739
identifying a tradition 740–1
and methodological concerns 742–3
assessing causation with small N 746–8
generalization 743–4, 745
scope 743–4, 745
selection bias 743
and misunderstanding of 738
and multimethod research 749–51
and origins of 737
and process tracing 747
and publications 738
and statistical analysis:
combining methods 749–50
comparison of types of knowledge sought 748–9
differences between 738, 739, 746
different research goals 745, 746
implications of differences between 748–51
missing variables 744–5
and traits of 739–40
comparisons, and typologies 162–3
COMPASS Research Group 789–90
competition, and interdependence 572, 574
complexity:
and agent‐based modeling 91
and qualitative comparative analysis 725–6
compliance, and Neyman‐Rubin‐Holland (NRH) theory 274
computational models 71–3
as agent‐based models 78–9
and examples of:
Baron‐Ferejohn bargaining 76–8
currency game 73–6
extending and complementing deductive results 75–6, 77
and requirements of 75
computer‐assisted personal interviewing (CAPI) 386, 395
computer‐assisted telephone interviewing (CATI) 348, 386
computer technology, and expansion of experimentation 340
concepts:
and construction/evaluation of 97–8
aggregation and structuring issues 98–103
checklist for 114–15
extreme points 105–6
homogeneity of negative or zero cases 111–14
homogeneity question 109–10
ideal types 105–6
middle points (‘gray zone’) 107–9
zero points 103–5
and formation of 158–9
and international conflict 100–1
and measurement of 7–8
and multidimensionality 9–10
and typologies 8–9
concept formation 158–9
Concomitant Variation, Method of 234, 246, 288
conditional logit models, and discrete choice methods 514
unordered choices 521
conditional probability 272, 282, 292
and counterfactuals 272
and inductive inference 290–2
confidence intervals 201, 502, 503
confirmation theory, and epistemology 56
conflict 5
and social theory 38
consistent adjusted least squares (CALS) 134
Consortium on Qualitative Research Methods (CQRM) 28
construct validity 122, 344
constructivism 782–3
and ontology 62–3
content validity 121
contextual effects, and spatial interdependence 571
contractarianism 38–9
controls, and experiments 342
convergent validity 8, 121
Cook's distance 658
cooperation, and surveys 390–1
coordination theories:
and institutional coordination 43, 44
and rise in causal thinking 6
and shared‐value theories 43
and social theory 42–4
and spontaneous coordination 43–4
correlation analysis 6
and comparative research 724, 725
and set‐theoretic arguments 196
correlation coefficients 199, 200
and comparing concepts and measures 107–8
correlation matrix, and psychometrics 200–1
Costa Rica 107, 110
counterfactuals 641–2
and case studies 628–9, 631
(p. 865)
and causal inference 13, 23–4
and causality 220–1, 232–3, 290, 629
closest possible worlds 234, 236–7
common causes 238
controlled experiments 236–7
evaluating counterfactual statements 234
Lewis's approach 233–5
pre‐emption 241–2
problems with definition 237–8
temporal precedence 238
virtue of definition of 235–6
and conditional probability 272
and criteria for evaluating 632–3, 641
clarity of antecedents and consequents 633–4
conditional plausibility of the consequent 638–40
connecting principles 635
consistency with empirical evidence 639
consistency with theory 638–9
cotenability 635
enabling counterfactuals 635
plausibility of the antecedent 634–8
projectibility 639
proximity 640
and definition of 220, 629
and game theory 630, 637
and historical debates 630
idiographic 631
and importance of 629–32
and inductive inference 290–2
as method 629
and minimal rewrite 635–6
and moral judgment 631–2
and nature of propositions 633
and necessary conditions 629–30
and pedagogical uses of 632
in political science 629–30
and redirecting counterfactuals 640
and skepticism about utility of 628
and theory development 632
and theory testing 631
and truth of 220
and unavoidability of 628
and use of 627
and validating claims of 628
and validity of counterfactual statements 234, 630–1
covariate balance 281, 363, 364
and experiments 376
covering laws:
and asymmetry problem 65
and explanation 64–5
Cox models, and survival analysis 531, 534, 544
handling of proportional hazards assumption 536–9
handling tied data 539–40
reliable treatment of baseline hazard 534–6
Cronbach’s alpha 124
cross‐level inference, see ecological inference
cross‐level interactions, and multilevel models 612–13
cross‐sectional surveys 389, 396–7
cross‐validation, and assessing heterogeneity 483–4
Cuban Missile Crisis, and counterfactuals 634–5
cultural theory, and typologies 162
cum hoc ergo propter hoc (‘with this, therefore because of this’) 293–4
currency game, and computational models 73–6
data augmentation 506
data clustering 607–8
data collection 16–17
Data Set Observations (DSOs) 301
databases 16
data‐generating process (DGP) 341
and Bayesian approach 495
and data augmentation 506
and econometrics 405
and external validity 345
and linear model 406
decision theory 832
deductive logic 56
degrees of freedom 718–19
and case studies 711
democracy:
and calibrating degree of membership 194–6
and dyadic concepts 100–1
and measurement difficulties 107–9, 110, 111–14
and typology of 160
democratic peace 476, 661
descriptive inference:
and regression‐like methods 17
and rise in causal thinking 18–19
desires, and individual actions 326
desires, beliefs and opportunities (DBO) theory 326
determinism, and causality 225, 288–9
developed countries, and calibrating degree of membership 194–6
direct method 186–90
indirect method 190–3
developmental historicism 6
and modernist empiricism 51
Deviance Information Criterion 506
Dickey‐Fuller tests 461
Difference, Indirect Method of 287–8
Difference, Method of 235, 240, 246, 284–7, 290
diffusion, and spatial interdependence 571
discontinuity designs 373–4
(p. 866) discrete choice methods 21–2, 513–14
and estimation 521–2
and heteroskedasticity 523–4
and interpretation 522
and literature on 527
and ordered choices:
more than two categories 516–18
two categories 514–16
and substitution patterns 524–7
and unordered choices:
more than two categories 520–1
two categories 518–20
discriminant validity 122
dissonance‐driven desire formation, and individual actions 328
distributive justice 44
doctrines, and meta‐methodology 50
duration dependence, and parametric models 540–1
Durbin‐Watson d 469–70
Duverger’s law 244
dynamic linear model (DLM), and measurement in dynamic setting 144–5
Eckart‐Young theorem 200, 202
ecological inference 547, 564–6
and approaches to:
continuum of 552
point estimates 553–8
ranges 552–3
and fundamental indeterminacy 549–51, 564–6
and individual behavior 547
and mathematics of 548
and methodological practice 566
and models:
aggregated multinomial model 556–7
assumptions 554, 555–6
neighborhood model 556
philosophy behind 557–8
random effects model 557
testing assumptions 558
and partial identification 558–9
assumptions and instrumental variables 561–2
distribution of interest 559
inference using data alone 559–61
structural prediction 562–4
and problem of 547
examples of 547–8
and racial voting 549–51
aggregated multinomial model 556–7
inference using data alone 559–61
neighborhood model 556
point estimates 554–5
random effects model 557
ranges 552–3
testing model assumptions 558
and related problems in other disciplines 548
econometrics, and political science:
data‐generating process (DGP) 405
and fixed treatments and endogeneity 406–8
instrumental variables estimator 410–13
representatives' deviations and electoral margins 413–16
instrumental variables in practice 416–17
correlations of instruments and endogenous variables 417–18
(p. 867)
independence of instruments and stochastic terms 418–20
linear model and observational data 405–6
maximum likelihood estimation (MLE) 405
OLS estimates 409–10
use of techniques in 405
Economics and Politics 339
election studies 798–800
and feeling thermometers 205–7
and unfolding analysis 206–7
elections, and agent‐based models of 79
agents as rule‐based objects 81–2
describing candidate and voter behavior 80–1
following rules vs maximizing utility 82–4
Empirical Implications of Theoretical Models (EITM) 828
and closing theory‐empiricism gap 829, 840
and controversy over 830
and development in political science 829, 830–5
and emphasis of 839–40
and evaluating models 840–1
and goal of approach 841
and initial use of 828
and interpretations of approach 835–7
Achen's approach 837–8
McKelvey's approach 838–9
and National Science Foundation 828, 829
and training 28–9, 828, 829–30, 840
empiricism, and political science 55 see also modernist empiricism
emulation, and interdependence 572–3
encyclopedias 822–3
endogeneity 404, 428–9
and comparison of estimators 425–8
and fixed treatments 406–8
and full information estimation 420–1
legislative politics 424–5
maximum likelihood 422–4
three‐stage least squares 421–2
and instrumental variables estimator 410–13
representatives' deviations and electoral margins 413–16
and instrumental variables in practice 416–17
correlations of instruments and endogenous variables 417–18
independence of instruments and stochastic terms 418–20
and OLS estimates 409–10
and regression analysis 19
epistemology 5, 55
and Bayesianism 58–9
and causality 225–6
and comparing theories 59
and confirmation theory 56
and falsificationism 56–7
and issues for political science 59–60
and meaning holism 57–8
and rational choice theory 54
equal percent bias reduction (EPBR) 277, 281, 294
equilibria, and game theory 87–8
error correction models (ECMs), and time‐series 467–8
Essex, University of, and Summer School in Social Science Data Analysis and Collection 790, 797
estimation 428–9
and comparison of estimators 425–8
and discrete choice methods 521–2
and full information estimation 420–1
legislative politics 424–5
maximum likelihood 422–4
three‐stage least squares 421–2
and instrumental variables 410–13, 416–17
correlations of instruments and endogenous variables 417–18
independence of instruments and stochastic terms 418–20
representatives' deviations and electoral margins 413–16
and maximum likelihood 495–6
and multilevel models 613–15, 617, 619
and quasi‐likelihood methods 617
and shrink estimators 618
and spatial error models 586–7
and spatial lag models 580–2
spatial maximum likelihood 585–6
spatial OLS 582–3
spatial‐2SLS and spatial‐GMM 583–5
and structural equation models 447–8
full information estimators 439–40
limited information estimators 440–1
and time‐series cross‐sectional (TSCS) methods 478–9
and two‐step approach 615, 618, 619–20
eugenics 199
event history, and time‐series cross‐sectional (TSCS) methods 487–9
Event Structure Analysis (ESA) 732
exchange theories:
and rise in causal thinking 6
and social theory 39
exclusion restriction 364, 368–9, 370–1
exit, voice and loyalty typology 157
expected utility, and international conflict 103–4
experimental data, differences from observational data 341
experiments:
and attrition 16
and causality 15–16, 247–9, 351
counterfactuals 236–7
manipulation 239–41
pre‐emption 241–2
and data‐generating process (DGP) 341, 345
and experimental data 341
and external validity 15
and features of:
control 342
natural experiments 343
random assignment 342–3
simulations 343
and field experiments 15, 357–8
attrition 372–3
classification of 359
definition of 358–9
growth and development of 359–62
and inference 362–5
contrasting experimental and observational 365–7
and location of 346
field experiments 346, 347–8
internet 347–8
laboratory 346–7
survey experiments 347–8
and methodological issues:
balance and stratification 375–6
covariates 376
extrapolation 377–8
power and replication 378
publication bias 377
and methodological testing 352–3
and methodological value of 378–9
and myth of the ideal 340–1
and natural experiments 15, 16, 373–4
and need for theory in 351–2
and noncompliance 16, 367–72
estimating treatment effects 371–2
exclusion restriction 368–9, 370–1
monotonicity 369, 371
nonzero causal effects of assignment on treatment 369–70, 371
Stable Unit Treatment Value Assumption (SUTVA) 369, 371
and policy‐makers 353
in political science 339–40
and political science 354, 359–62
and quasi‐experiments 239–40
and searching for facts 350–1
(p. 868)
and survey experiments 347–8, 358–9
and theory testing:
formal models 349–50
nonformal theories 348–9
and validity 343–4
external validity 344–5
explanation:
and asymmetrical nature of 65
and forms of 64
covering laws 64–5
historicism 66–7
reasons as causes 65–6
and meaning holism 66–7
and mechanisms 321, 332–3
individual actions 325–9
macro‐level outcomes 329–32
and rational choice theory 54
in social research 12–15
external forces, and survey methodology 397–8
external validity, and experiments 15, 344–5
extrapolation, and experiments 377–8
extreme points, and construction/evaluation of concepts and measures 105–6
face‐to‐face surveys 386, 390–1, 395
factor analysis 128–35
and correlation matrix 200
and Eckart‐Young theorem 202
and estimation and inference via maximum likelihood 132–3
and estimation via principal components 131–2
and identification constraints 130–1
and inference for latent variables 133–4
and inference with latent variables 134–5
and origins of 200–1
and roll‐call voting 205
falsificationism, and epistemology 56–7
Fashoda crisis 703, 706
and affirmative evidence 712
and eliminative induction 712
feasible generalized least squares (FGLS) 480, 481
feeling thermometers 205–6
field experiments 15, 346, 347–8, 357–8
and attrition 372–3
and classification of 359
and definition of 358–9
and growth and development of 359–62
and inference 362–5
contrasting experimental and observational 365–7
and methodological issues:
balance and stratification 375–6
covariates 376
extrapolation 377–8
power and replication 378
publication bias 377
and methodological value of 378–9
and noncompliance 367–72
estimating treatment effects 371–2
exclusion restriction 368–9, 370–1
monotonicity 369, 371
nonzero causal effects of assignment on treatment 369–70, 371
Stable Unit Treatment Value Assumption (SUTVA) 369, 371
First World War:
and counterfactuals 627, 636, 640
and German policy 703
and process tracing 707
fixed effects, and time‐series cross‐sectional (TSCS) methods 483
fluoridation 309–10
folk psychology 66
forecasting, and parametric models 541–2
Freedom House 108, 110
free‐rider model 329
free‐riding, and interdependence 574
FSQCA (software package) 728 see also qualitative comparative analysis (QCA)
full information estimation 420–1
and legislative politics 424–5
and maximum likelihood 422–4
and structural equation models 439–40, 447–8
and three‐stage least squares 421–2
full maximum likelihood estimation (FMLE) 614
functional equivalence 109
fundamental indeterminacy, and ecological inference 549–51, 564–6
fuzzy‐set analysis 182–3, 197
and basic idea of 174–5
as bridge between qualitative and quantitative approaches 182–3
and calibration 174, 175, 183
direct method 186–90
indirect method 190–3
techniques of 184
use of calibrated measures 193–6
and conventional variables 183
and fuzzy‐set qualitative comparative analysis (fsQCA) 174, 730, 732
and qualitative comparative analysis 174, 730–2
and relevant/irrelevant variation 183
and transforming interval‐scale variables 184–6
Galton's problem 574–5, 679
game theory 23, 45, 832
and Baron‐Ferejohn bargaining 76–8
and computational models, currency game 73–6
and counterfactuals 630, 637
(p. 869)
and difference from agent‐based models 82–4
and equilibria 87–8
Gauss‐Markov assumptions 478, 480
generalized latent variable modeling 137–9
generalized least squares (GLS) 470
Generalized Linear Latent and Mixed Modeling Framework (GLLAMM) 452
genetic matching 279–81
German measles 311
Gibbs sampling algorithm 498–9, 617
globalization, and interdependence 572
Granger causality 466
group‐level predictors, and multilevel models 611–12
Gulf War (1991) 713–14
Guttman Scaling 204, 205
happiness, and aggregation 99–100, 102
hat matrix 658
hazard rate, and survival analysis 531
heteroskedastic probit model 524
heteroskedasticity:
and discrete choice methods 523–4
and multilevel models 606
hierarchical modeling 22
historical analysis, see comparative‐historical analysis
historical explanation 703–4
and competing 703
and counterfactuals 628
and end of cold war 715–18
and process tracing 704
historical institutionalism 52–3
historicism, and explanation 66–7 see also developmental historicism
homogeneity, and construction/evaluation of concepts and measures 109–10
negative or zero cases 111–14
homoskedasticity 123
Huber‐White estimator 607
Human Development Index 175 n1
hyperfactualism 52, 69
hypermethodologism 69
hypothesis testing 502, 503
and vector autoregression 466
ideal types:
and construction/evaluation of concepts and measures 105–6
and typologies 161–2
identification, and structural equation models 438–9, 447
implied moment matrices, and structural equation models 436–8
independence of irrelevant alternatives (IIA) 525
independently and identically distributed (IID) 525
indicators, and measurement practices in quantitative research 177–9
individualism, and exchange theory 39
individuals:
and ecological inference problem 547
and mechanism‐based explanation of actions 325–9
dissonance‐driven desire formation 328
‘Old Regime’ pattern 328–9
rational imitation 328
self‐fulfilling prophecy 328
sour‐grapes syndrome 326
vacancy chains 328
wishful thinking 326
and political philosophy 35
and social science inquiry 5
induction 55
inductive inference:
and conditional probability 290–2
and counterfactuals 290–2
and Mill's methods:
conditions 282
Indirect Method of Difference 287–8
Method of Agreement 284
Method of Difference 284–7
infectious diseases 323
informative priors 504
innovation accounting 466
Institute for Qualitative and Multimethod Research 786–9
and overview of 787–9
and support for advanced research on methodology 789
institutionalism, and traditions of political science 52–3
institutions:
and diffusion of 571
and economic outcomes 406
and political methodology 28
instrumental variables 19, 428, 429
and ecological inference 561–2
and estimator of 410–13
representatives' deviations and electoral margins 413–16
in practice 416–17
correlations of instruments and endogenous variables 417–18
independence of instruments and stochastic terms 418–20
intentionality 65
intention‐to‐treat (ITT) 274, 367
interaction terms, and zero points 105
interdependence, see spatial interdependence
interest representation, and typology of 160
(p. 870) inter‐item reliability 124
intermediation, and typology of 160
internal validity 344
international conflict:
and aggregation 100–1
and dyadic concepts 100–1
and expected utility theories 103–4
International Organization 790
international political economy, and interdependence 572
International Political Science Association (IPSA), and Committee on Concepts and Methods 789
international relations:
and interdependence 571–2
and rivalry/reciprocity 407
International Typographical Union (ITU) 658
internet:
and experiments 347–8
and surveys 386, 388–9, 395
interpretation, and discrete choice methods 522
interpretativism 782–3
inter‐rater reliability 123–4
interstate rivalry, and aggregation problem 102
Inter‐University Consortium for Political and Social Research (ICPSR) 28
and creation of 800
Summer Program 796, 797, 800–2
continuing demand for 805–8
curriculum 804–5
development of 798–804
interviews 25, 700
and lack of attention to 686
and practical difficulties 685
and pragmatic case for 690–5
accuracy of answers 694
advantage over memoirs and archives 691
establishing causation 692
establishing motivation and preferences 690–1
establishing structural causes 691
factual status 691–2
gauging bias 695
indirect questions 693
nature of questions 692–4
overcoming strategic reconstruction 694–5
productive approach 690
suitability for subject 690
and purpose of 688
and semi‐structured interviews:
and skepticism about 685–6, 687–90
behavioralist approaches 687–8
objectivity 687, 688–9
rational choice approaches 687, 688–9
relativism 689–90
respondent dissembling 689
scientific status of data 688
strategic reconstruction 689
theory‐driven research 687, 688
and techniques 695
asking for other contacts 699
building on successive interviews 699
demonstrate professionalism 698
establishing contacts 696–7
follow‐up questions 699
knowledge of role of interviewee 698
nature of questions 698
openness 696
order of questions 699
preparation 695–6
questionnaire 698–9
recording 697–8
and underuse of 685
failure to teach 686
methodological objections 685–6
intraclass correlation, and multilevel models 607
intrapersonal variables, and survey methodology 398–400
INUS conditions, and causality 227–9, 230–1
invention, and rise in causal thinking 6
isomorphism 377
issue voting, and typology of 157, 166
item response theory 135–7, 505
Journal of Conflict Resolution 339, 815
Journal of Mixed Methods Research 791
Journal of Politics 339, 815
Journal of Theoretical Politics 790
journals 790
general 815–17
specialized 818–19
JSTOR 16
and categorization 8
and causal inference 4
justice:
and changed meaning of 44
and interest 37
Kalman Filter, and measurement in dynamic setting 144–5
Katrina, hurricane 343
kind hierarchy, and typologies 158, 159
Kwiatowski‐Phillips‐Schmidt‐Shin (KPSS) test 461
laboratory experiments 346–7
large‐n correlational analysis 26
latent class models 139–40, 141–2
latent response formulation, and structural equation models 444–5
latent variables 119, 120
and discrete choice methods 513
(p. 871)
and measurement error 120–1, 123
costs of ignoring 126–8
and measurement models:
factor analysis 128–35
generalized latent variable modeling 137–9
inference for discrete latent variables 139–42
item response theory 135–7
time‐series 144–5
Wiley‐Wiley model 142–3
and measurement reliability 122–5
and measurement validity 121–2
and structural equation models 432
specification and assumptions 433–4
and uses of measures of 125–6
Latin America, and typology of political parties 158
learning, and interdependence 572
legislative politics:
and comparison of estimators 425–8
and full information estimation 424–5
and instrumental variables estimator 413–16
and margins and deviations 409–10
and representation 407, 408
level‐1 coefficients, and multilevel models 618–19
liberalization, and cross‐national diffusion 572
likelihood functions 504
limited information estimators, and structural equation models 440–1, 447–8
linear model 405–6
and data‐generating process (DGP) 406
and fixed treatment and endogeneity 406–8
and instrumental variables estimator 410–13
representatives’ deviations and electoral margins 413–16
and instrumental variables in practice 416–17
correlations of instruments and endogenous variables 417–18
independence of instruments and stochastic terms 418–20
and OLS estimates 409–10
linear regression model 495, 497
LISREL 19, 452–3
and structural equation models 433
lme4 (software package) 616
logical positivism 50
and confirmation theory 56
and explanation 64
and verification 61
logit models, and discrete choice methods 513, 514
ordered choices 516
unordered choices 520
lung cancer 218
macro‐level outcomes, and mechanisms 329–32
Mahalanobis distance 277, 278–9
major power status, and international conflict variables 101
manipulation 13
and causality 239–41
marginal quasi‐likelihood (MQL) 617
Markov Chain Monte Carlo (MCMC) methods 21, 207–8, 494, 504–5
and posterior distributions 497–501
Markov transition models, and time‐series cross‐sectional (TSCS) methods 490
matching methods 271–2, 277
and case studies 281–3
deterministic methods 282
and genetic matching 279–81
and Mahalanobis distance 278–9
and Mill's methods 282, 283–4, 288
conditions 282
Indirect Method of Difference 287–8
Method of Agreement 284
Method of Difference 284–7, 290
and propensity score matching 278–9
and unit homogeneity 272
mathematical modeling, and comparison with agent‐based modeling 89–91
maximum likelihood estimation (MLE) 405, 495–6
and factor analysis 132–3
and full information estimation 422–4
and multilevel models 614
and spatial lag models 585–6
Maxwell School (Syracuse University) 789
MCMCpack (software package) 508
meaning holism 55, 68
and beliefs 62
and causation 65–6
and constructivism 62–3
and epistemology 57–8
and explanation 66–7
and ontology 62–3
measurement:
and calibration 9, 174
and common practices:
qualitative research 180–2
quantitative research 177–9
and concepts 7–8
and fuzzy‐set analysis as bridge between qualitative and quantitative approaches 182–3
and goals of 120–1
and latent variables 119, 120
and measurement error 120–1, 123
costs of ignoring 126–8
and multiple indicators 125
and reliability 120, 122–5
inter‐item reliability 124
inter‐rater reliability 123–4
test‐retest reliability 123
(p. 872)
and rise in causal thinking 7–12
and uses of 125–6
and validity 120, 121–2 see also calibration
measurement models 119, 128
in dynamic settings 142
time‐series 144–5
Wiley‐Wiley model 142–3
and factor analysis 128–35
estimation and inference via maximum likelihood 132–3
estimation via principal components 131–2
identification constraints 130–1
inference for latent variables 133–4
inference with latent variables 134–5
and generalized latent variable modeling 137–9
and inference for discrete latent variables 139–42
and item response theory 135–7
and latent class models 139–40, 141–2
and mixture models 140–2
and restrictions on 125
measurement problems 119
measures, and construction/evaluation of 97–8
aggregation and structuring issues 98–103
checklist for 114–15
extreme points 105–6
homogeneity of negative or zero cases 111–14
homogeneity question 109–10
ideal types 105–6
middle points (‘gray zone’) 107–9
zero points 103–5
mechanisms 13, 319
and causality 243–5, 246–7, 292–3, 320
multiple causes 246
and definition of 321, 322
and empirical research 332
and explanation 14
and individual actions 325–9
dissonance‐driven desire formation 328
‘Old Regime’ pattern 328–9
rational imitation 328
self‐fulfilling prophecy 328
sour‐grapes syndrome 326
vacancy chains 328
wishful thinking 326
and macro‐level outcomes 329–32
and mechanism‐based explanation 321–4, 332–3
and networks 322–3
and quantitative research 324–5
and reasons for focusing on 323
and social structure 322–3
and statistical inference 320
medicine:
and case studies 293
and qualitative reasoning 301, 312–13
Eijkman and beriberi 306–8
Fleming and penicillin 310–11
Goldberger and pellagra 308–9
Gregg and German measles 311
Herbst and AIDS 312
Jenner and vaccination 301–2
literature 313–16
McKay and fluoridation 309–10
Semmelweis and puerperal fever 302–4
Snow and cholera 304–6
Merchant's Rule of Three 457
meta‐methodology 48–9
and concepts 49–50
doctrines 50
subfields 49
traditions 49
and epistemology 55
Bayesianism 58–9
comparing theories 59
confirmation theory 56
falsificationism 56–7
issues for political science 59–60
meaning holism 57–8
rational choice theory 54
and forms of explanation 64
covering laws 64–5
historicism 66–7
reasons as causes 65–6
and importance of 48
and ontology 60
constructivism 62–3
naive realism 60–1
ontological commitment 61–2
and traditions of political science 50
behavioralism 52
institutionalism 52–3
modernist empiricism 51
rational choice theory 53–4
Metropolis‐Hastings algorithm 498, 499–500, 617
Michigan election studies 799
Michigan Political Behavior Program 799
Michigan Survey Research Center 799
Midwest Journal of Political Science 815
migration, and interdependence 573
missing data, and Bayesian approach 506
mixed logit model, and discrete choice methods 526
mixture models 140–2
model comparison, and Bayesian approach 505–6
model fit, and structural equation models 441–2
modernist empiricism 6
and political science 51
modifiable area unit problem (MAUP) 548
(p. 873) monotone regression 204
monotonicity, and experiments 369, 371
most different design 283
most similar design 283
Moynihan Institute of Global Affairs 789
multidimensional scaling (MDS) 202–4, 205–6
multidimensional typologies, see typologies
multidimensionality, and concepts 9–10
multilevel data 476, 605–6
and pooling 606–8
multilevel models 23, 605, 608–9, 619–20
and Bayesian approach 614–15
and binary response model 616
and cross‐level interactions 612–13
and data clustering 607–8
and estimation issues 613–15, 617, 619
and extensions of 615–17
and group‐level predictors 611–12
and intraclass correlation 607
and level‐1 coefficients 618–19
and multilevel data 605–6
pooling 606–8
and origins of 605
and random coefficient models 609–11
and random slopes 611–12
and structural equation models 451–2
multimethod research:
and comparative‐historical analysis 749–51
and growing popularity of 758
and narrative choice:
convenience samples 762
‘good cases’ 761–2
random selection 758, 764–6
selection bias 761
structuring the narrative 766–8
variation in the dependent or independent variables 762–4
multinomial logit models, and discrete choice methods 514, 521, 525, 527
unordered choices 521
naive realism, and ontology 60–1
narratives:
and case studies 757–8
and choice of 761
convenience samples 762
‘good cases’ 761–2
random selection 764–6
selection bias 761
variation in the dependent or independent variables 762–4
and civil war onset 773–4
learning from 770–3
random selection 765–6
structuring the narrative 766–8
National Science Foundation 28, 348, 789, 828, 829
natural experiments 15, 16, 343, 373–4
necessary conditions:
and causality 630
and comparative research 724
and counterfactuals 629–30
neighborhood model, and ecological inference 556
networks:
and agent‐based modeling 84–6
and mechanisms 322–3
new institutionalism 53
newsletters, specialized 819–20
Neyman‐Rubin model, see Neyman‐Rubin‐Holland (NRH) theory
Neyman‐Rubin‐Holland (NRH) theory, and causation 13, 249–51, 266–7, 271, 272–3, 362–5
average causal effect (ACE) 261–4
average treatment effect (ATE) 362–3
average treatment effect among the treated (ATT) 275–6, 362–3
causal priority 253
counterfactual definition of causal effect 250
creation of mini‐possible worlds 250
experimental data 273–5
bias 275
compliance 274
randomization 273–4, 275, 363
identicality of counterfactual situations 250
independence of assignment and outcome 250, 253–6
intention‐to‐treat (ITT) 274
matching methods 277
genetic matching 279–81
Mahalanobis distance 278–9
propensity score matching 278–9
multiplying number of units 264
observable definitions of causality 256–61
observational data 275–7
average treatment effect (ATT) 275–6
dropping observations 276
ontological definition of causal effect based upon counterfactuals 251–3
origins of 273
Stable Unit Treatment Value Assumption (SUTVA) 250, 265–6, 274, 364–5
NOMINATE 205, 207
noncompliance, and experiments 16, 367–72
estimating treatment effects 371–2
exclusion restriction 368–9, 370–1
(p. 874)
monotonicity 369, 371
nonzero causal effects of assignment on treatment 369–70, 371
Stable Unit Treatment Value Assumption (SUTVA) 369, 371
nonformal theories 348
nonstationary data, and time‐series cross‐sectional (TSCS) methods 479–80
normative political theory 3
normative social theory 35–6
norms, and shared‐value theories 41–2
numerical optimization 504
observational data 14
and combining observations 292
and dropping observations 276
and experimental data, differences from 341
and linear model 405–6
and Neyman‐Rubin‐Holland (NRH) theory 275–7
average treatment effect among the treated (ATT) 275–6
observational inference, and contrasted with experimental inference 365–7
‘Old Regime’ pattern, and individual actions 328–9
omitted variable problem 548
ontology 5, 60
and causality 224–5
and constructivism 62–3
and meaning holism 62–3
and naive realism 60–1
and ontological commitment 61–2
and rational choice theory 54
opinions, and surveys 393–4
mode of data collection 394–5
panels 396
opportunities, and individual actions 326
ordered logit models, and discrete choice methods 513–14
ordered choices 518
ordered probit models, and discrete choice methods 513–14
ordered choices 517
ordinary least squares (OLS), estimates 409–10
organizations:
and political methodology 28, 796–7, 810–12
and qualitative and multimethod research 783–90
and quantitative methodology 796–7, 799–808
overarching concept 159
and typologies 162–3
panel corrected standard errors (PCSEs) 480, 481
panel data:
and spatio‐temporal models for 593–6
and surveys 388–9, 392, 396, 398, 399–400
paper and pencil surveys 386
parameter estimation 120, 125
parameter instability, and time‐series models 469
parametric models, and survival analysis 531, 540
duration dependence 540–1
flexible parametric models 542
forecasting 541–2
partial identification 549
and ecological inference 558–9
assumptions and instrumental variables 561–2
distribution of interest 559
inference using data alone 559–61
structural prediction 562–4
partial‐autocorrelation functions (PACF) 459
party‐competition model 329
patriotism 40–1
pellagra 308–9
penalized quasi‐likelihood (PQL) 617
penicillin 310–11
Perspectives in Politics 783
point estimates, and ecological inference 553–8
Poisson autoregressive (PAR) model 470
Poisson exponentially weighted moving average (PEWMA) model 470
policy diffusion, and spatial interdependence 571
policy implementation, and typology of 153–7, 159, 160
policy‐makers, and experiments 353
Political Action Data 448
Political Analysis 811, 818–19, 822, 824, 834
Political Behavior 339
political economy, and typology of 164
political efficacy, and structural equation models 448–51
Political Methodologist 819–20, 822, 824
Political Methodology 809, 810, 818
political methodology:
and changes in field 29
and development of 808–10
and developments in political science 830–5
and functions of 3–4
and training 28, 785, 787–8, 812
summer programs 797–808
political parties, and typology of 158, 163–4
political philosophy, and origins of 35
Political Psychology 339
Political Research Quarterly 790
political science:
and causality 4–5
and developments in 829, 830–5
and traditions of 50
behavioralism 52
institutionalism 52–3
modernist empiricism 51
rational choice theory 53–4
pooling, and multilevel data 606–8
positivism 50
posterior distributions:
and Bayesian approach 21, 496, 497–501
and Monte Carlo method 497–8
and multilevel models 617
poverty research, and calibration 175 n1
precision:
and fuzzy‐set analysis 182
and measurement 122
predictive validity 121
pre‐emption, and causality 241–2
Principal Component Analysis 200
probabilism, and causality 225, 289
probability:
and Bayesian approach 495
probit analysis 166
probit models, and discrete choice methods 513, 514
ordered choices 516
unordered choices 519–20
process tracing 25–6, 292
and affirmation of hypotheses 711
and Bayesian analysis 702, 718–19
differences between 708, 714
similarities 708, 719
and changing status of case 706
and comparative‐historical analysis 747
and elimination of hypotheses 711
and end of cold war 715–18
and end of First World War 707
and evidence tests:
doubly decisive tests 706
hoop tests 706
smoking gun tests 706
straw in the wind tests 706
and Fashoda crisis 712
and generalizing from one/few cases 713–14
and good practice 707
and historical explanation 704
and level of analysis/detail 705
and limitations of 712–13, 719
and nature of 704
and nature of evidence 709–10
and provisional nature of 705
and theoretical explanation 704
and theory generation 704, 705
and theory testing 704–5
and underdetermination thesis 712–13
and uses of 702
propensity score matching 272, 277, 278–9
proportional hazards assumption, and Cox models 536–9
Psychometric Society 202
psychometrics 199
and common measurement practices 178
and correlation matrix 200–1
and Eckart‐Young theorem 202
and factor analysis 200–1
and feeling thermometers 205–7
and influence on political science 205–8
and multidimensional scaling 202–4
and origins and development of 199–202
and response functions 203–4
and scalogram analysis 204, 205
and unfolding analysis 204–5, 206–7, 208
Psychometrika 202, 203
Public Choice 339
Public Opinion Quarterly 339
publishing 824–5
and changes in 824
and encyclopedias 822–3
and journals:
general 815–17
specialized 818–19
and ‘missionaries’ or ‘theologians’ 824
and opportunities for 824–5
and publication bias 377
and qualitative and multimethod research 790–1
and quantitative political methodology 28, 809–10, 814
and quantitative political research 814–15
and Sage Quantitative Applications in the Social Sciences 821–2
and specialized newsletters 819–20
and textbooks 823
puerperal fever 302–4
qualitative and multimethod research 780
and meaning of multimethod 780–1
diverse approaches within conventional qualitative methods 781–2
linking qualitative, quantitative and statistical tools 782
relationship with interpretativism and constructivism 782–3
and organizations in support of 783–4, 789–90
Institute for Qualitative and Multimethod Research 786–9
Qualitative and Multi‐Method Research Section of the APSA 784–6
and publication 790–1
and quantitative research, integration with 791–2
qualitative comparative analysis (QCA) 26, 723
and applications of 727–8
(p. 876)
and best practices 728–9
and case study methods 734
and combination with other methods 728, 734
and complex causation 725–6
and debates about 733
and dissemination of 734
and fuzzy‐set analysis 174, 730–2
and fuzzy‐set qualitative comparative analysis (fsQCA) 730, 732
and innovations in 732–3
and micro‐level cases 734
and MSDO/MDSO procedure 733
and multi‐value QCA (mvQCA) 730
and potential of 734–5
and software for 728, 733–4
and specific connections 725
and temporality 732–3
and truth tables 726–7
interpretation 729
limitations of 730
and two‐step procedure 733
and uses of 723, 728
qualitative literature, and structuring concepts 99
qualitative reasoning, and scientific enquiry 301, 312–13
Eijkman and beriberi 306–8
Fleming and penicillin 310–11
Goldberger and pellagra 308–9
Gregg and German measles 311
Herbst and AIDS 312
Jenner and vaccination 301–2
literature 313–16
McKay and fluoridation 309–10
Semmelweis and puerperal fever 302–4
Snow and cholera 304–6
qualitative research:
and common measurement practices 180–2
calibration 180
case oriented 180–1
external standards 181–2
iterative nature of 180
and eclecticism of 780
and Mill's methods 283–4, 288
conditions 282
Indirect Method of Difference 287–8
Method of Agreement 284
Method of Difference 284–7, 290
and quantitative research 781
and research design 282
and resurgence of 779–80
qualitative tools, and causal inference 23–6
quantitative literature, and aggregation 99
quantitative methodology:
and agent‐based modeling 331
and common measurement practices 177–9
indicators 177–9
psychometric theory 178
relativity 178–9
structural equation modeling 178
and development of 798–800, 808–10
and general methods 16–21
and mechanisms 324–5
and role of organizations 796–7, 799–808
and special topics 21–3
and statistical inference 324–5
and summer programs 797
continuing demand for 805–8
curriculum 804–5
development of 798–804
and typologies of quantitative analysis 165–6
quantitative research:
and explaining results 757
and qualitative and multimethod research, integration with 791–2
and qualitative research 781
quantities of interest, and Bayesian approach 503–4
quantum mechanics 225
quasi‐experiments 239–40
quasi‐likelihood methods, and estimation 617
Quine‐Duhem problem 712–13
R language 508, 616
racial voting, and ecological inference 549–51
aggregated multinomial model 556–7
inference using data alone 559–61
neighborhood model 556
point estimates 554–5
random effects model 557
ranges 552–3
testing model assumptions 558
railroads, and counterfactuals 635
random assignment 363
and experiments 342–3
random coefficient models (RCM) 526
and multilevel models 609–11
and time‐series cross‐sectional (TSCS) methods 484–6
random digit dialing (RDD) techniques 388
random narratives 758
and civil war onset 765–6, 773–4
learning from 770–3
structuring the narrative 766–8
and narrative choice 762–4
random slopes, and multilevel models 611–12
random utility maximization (RUM) 518
ranges, and ecological inference 552–3
rational choice theory 45, 687, 688–9, 832
and epistemology 54
and explanation 54
and individual actions 326
and ontology 54
and traditions of political science 53–4
(p. 877) rational imitation, and individual actions 328
realism, see also naive realism
regimes, and typology of 157, 159, 164–5
regression analysis 6
and appeal of 24
and causal inference 12, 17
and descriptive inference 17
and instrumental variables 19
and rise in causal thinking 12–13, 14–15, 17–19
and spurious relationships 18–19
regression discontinuity 272, 373–4
relativity, and common measurement practices 178–9
reliability:
and assessing:
inter‐item reliability 124
inter‐rater reliability 123–4
test‐retest reliability 123
and measurement 9, 120, 122–5
research design 276–7
Residues, Method of 288
respecification, and structural equation models 442–3
response functions 203–4
response rates, and surveys 390–1, 392
restricted maximum likelihood estimation (RMLE) 614
revolutionary perspectives 5
roll‐call voting 205
and spatial model of 207
and unfolding analysis 207–8
rolling cross‐section (RCS) surveys 389, 397–8, 399
rules, and agent‐based modeling 81–2
Sage Publications 791
and Sage Quantitative Applications in the Social Sciences 821–2, 824
sample bias, and case selection 675 see also bias; selection bias
sampling, and surveys 387–8
scalogram analysis 204, 205
science:
and behavioralism 52
and falsificationism 57
scientific enquiry:
and nature of 300–1
and qualitative reasoning 301, 312–13
Eijkman and beriberi 306–8
Fleming and penicillin 310–11
Goldberger and pellagra 308–9
Gregg and German measles 311
Herbst and AIDS 312
Jenner and vaccination 301–2
literature 313–16
McKay and fluoridation 309–10
Semmelweis and puerperal fever 302–4
Snow and cholera 304–6
scientific thinking, and measurement of 11
seasonality, and time‐series models 462
Second World War, and counterfactuals 627, 631–2, 636
selection bias:
and comparative‐historical analysis 743
and narrative choice 761
and surveys 389, 391–2
self‐fulfilling prophecy, and individual actions 328
self‐interest 36–7
and rise in causal thinking 5
set theory:
and calibration 174
and comparative research 724
and correlational analysis 196
and social science theory 193–4, 197 see also fuzzy‐set analysis
shared‐value theories:
and coordination theories 43
and rise in causal thinking 5–6
and social theory 38–9, 40–2, 45–6
shrink estimators 618
Simpson's Paradox 548
simulations, and experiments 343
skepticism 55
smallpox 301–2
smoking 218, 293
social contract theory 38–9
social desirability, and survey responses 120
social outcomes, and mechanisms 329–32
Social Science Research Council 800
social structure, and mechanisms 322–3
social theory:
and conflict theories 38
and coordination theories 42–4
and creativity in 45
and exchange theory 39
and shared‐value theories 38–9, 40–2, 45–6
and social science methodology 5–6
social welfare, and aggregation 99–100, 102
Society for Political Methodology 29, 796, 810–12, 834
and origins and development of 797–8
software:
and Bayesian analysis 507–8
and discrete choice methods 522
and multilevel models 619
and qualitative comparative analysis 728, 733–4
sour‐grapes syndrome, and individual actions 326
Soviet Union 703
and end of cold war 715–18
space, and survey methodology 387–8
spatial analysis 22, 598
and calculating/presenting spatial effects 587–8
(p. 878)
and empirical‐methodological challenges of 574–6
common shocks 575
estimation difficulties 575
Galton's problem 574–5
model precision 575
spatial econometrics 575–6
spatial statistics 576
and model specification and estimation 578
estimating error models 586–7
estimating lag models 580–6
OLS with specification testing under the null 578–80
and spatial autoregressive models 576
combined lag and error models 577
with multiple lags 588–90
spatial error models 577
spatial lag models 577
and spatial models for binary outcomes 590
spatial error probit models 592–3
spatial log probit models 590–2
and spatio‐temporal models for panel data 593–6
spatial autoregressive models:
and calculating/presenting spatial effects 587–8
and combined lag and error models 577
and estimating error models 586–7
and estimating lag models 580–2
spatial maximum likelihood 585–6
spatial OLS 582–3
spatial‐2SLS and spatial‐GMM 583–5
with multiple lags 588–90
and OLS with specification testing under the null 578–80
and spatial error models 577
and spatial lag models 577
spatial econometrics 481, 575–6
spatial error models:
and estimation 586–7
and spatial analysis 577
spatial error probit models 592–3
spatial interdependence 22–3, 598
and empirical analyses of 570
political science 570–1
and general theoretical model of 573–4
and institutional diffusion 571
and mechanisms of 572–3
coercion 572
competition 572, 574
emulation 572–3
learning 572
migration 573
and policy innovation diffusion 571
and range of effects 571–2
and strategic interdependence 574
spatial lag models:
and estimation 580–2
spatial maximum likelihood 585–6
spatial OLS 582–3
spatial‐2SLS and spatial‐GMM 583–5
and spatial analysis 577
spatial lag probit models 590–2
spatial modeling:
and growth of interest in 570
and voting 201, 207
spline functions 542
stability, and equilibria 87–8
Stable Unit Treatment Value Assumption (SUTVA) 15
and experiments 369, 371
and Neyman‐Rubin‐Holland (NRH) theory 250, 265–6, 274, 364–5
stationary data, and time‐series cross‐sectional (TSCS) methods 478–9
statistical conclusion validity 344
statistical inference 320
and Bayesian approach to 495–7
and causal inference 320
and descriptive inference 17
and mechanisms 320
and quantitative research 324–5
strategic interdependence 573–4
stratification, and experiments 375–6
strikes, and typology of 165
Structural Equation Modeling: A Multidisciplinary Journal 135
structural equation models 10, 19, 432–3, 452–3
and categorical and discrete responses 443–4
application 448–51
estimation 447–8
generalized linear model formulation 446
identification 447
implied moments 446–7
latent response formulation 444–5
and characteristics of 432–3
and common measurement practices 178
with continuous responses 433–43
exogenous x form 436
full information estimators 439–40
identification 438–9
implied moment matrices 436–8
limited information estimators 440–1
model estimation 439
model fit 441–2
model specification and assumptions 433–6
respecification 442–3
and latent variables 125, 135, 432
and multilevel models 451–2
structural prediction, and ecological inference 562–4
structure, and construction/evaluation of concepts and measures 98–103
(p. 879) Studies in Comparative International Development 790
subfields, and meta‐methodology 49
substitution patterns, and discrete choice methods 524–7
sufficient conditions, and comparative research 724
summer programs in quantitative methods 797
and continuing demand for 805–8
and curriculum 804–5
and development of 798–804
survey experiments 347–8, 358–9
survey methodology 385, 400
and causality 396–7
external forces 397–8
intrapersonal variables 398–400
and data collection 16–17
and fieldwork choices 386
cross‐sectional surveys 389
mode of fieldwork 386
representation of space 387–8
representation of time 388–9
rolling cross‐section (RCS) surveys 389, 397–8, 399
sampling 387–8
and measurement error 120–1
and representing opinions 393–4
distribution of response 394
mode of data collection 394–5
panels 396
quality of response 393–4
and representing persons:
contacting 390
cooperation 390–1
coverage 390
panels 392
response rates 390–1, 392
selection bias 389, 391–2
unit nonresponse 389
surveys 385
survival analysis 22, 530–1
and advantages of Cox models 534, 544
handling of proportional hazards assumption 536–9
handling tied data 539–40
reliable treatment of baseline hazard 534–6
and grown in use of 530
and illusory benefits of parametric models 540, 543–4
duration dependence 540–1
flexible parametric models 542
forecasting 541–2
and key terms:
baseline hazard 531
hazard rate 531
state changes 532
and methodological practice 543
and model choice 543
Cox models 531
parametric models 531
time‐constant covariates (TCCs) 532
time‐dependent coefficients (TDCs) 532–4, 539
time‐varying covariates (TVCs) 532–4, 539
and questions addressed by 530
tax competition 574
telephone surveys 386, 390, 395
test theory model 9
test‐retest reliability 123
tetrad difference 200
textbooks 823
Theory and Society 790
theory evaluation 633
theory testing:
and Bayesian analysis 708–9
and counterfactuals 631
and experiments:
formal models 349–50
nonformal theories 348–9
three‐stage least squares 421–2
tied data, and Cox models 539–40
time:
and qualitative comparative analysis 732–3
and survey methodology 388–9
time‐constant covariates (TCCs), and survival analysis 532
time‐dependent coefficients (TDCs), and survival analysis 532–4, 539
time‐series analysis 470–1
and basic time‐series model 460
irregular components 462–3
moving average 460
seasonality 462
trends 461–2
and change 456
and dynamic nature of data 456
and history of 457–9
and measurement in dynamic setting 144–5
and modeling data:
ARMA and ARIMA models 463–5
data aggregation 469
error correction models (ECMs) 467–8
parameter instability 469
time‐series regressions 469–70
vector autoregression (VAR) 465–7
time‐series cross‐sectional (TSCS) methods 20–1
and applications 475
and binary dependent variables 486–7
event history approaches 487–9
Markov transition models 490
(p. 880)
and cross‐sectional issues 480
spatial insights 481–2
traditional approaches 480–1
and data 475–6
examination of 476–7
multilevel data 476
panel data 475
and dynamic issues:
estimation 478–9
nonstationary data 479–80
stationary data 478–9
and exploratory analysis 476–7
and growth of interest in 476
and heterogeneous units 482
assessing heterogeneity by cross‐validation 483–4
fixed effects 483
random coefficient models 484–6
and notation 477–8
time‐series regressions 469–70
and autocorrelation 20
and causal inference 12, 19–20
and rise in causal thinking 13
and spurious relationships 20
Time‐Sharing Experiments in the Social Sciences (TESS) 348
time‐varying covariates (TVCs), and survival analysis 532–4, 539
Tobler's Law 572
TOSMANA (software package) 728, 730
trade dependency, and international conflict variables 101–2
traditions, and meta‐methodology 49
training:
and Empirical Implications of Theoretical Models (EITM) 28–9, 828, 829–30, 840
and political methodology 28, 785, 787–8, 812
and summer programs 797
continuing demand for 805–8
curriculum 804–5
development of 798–804
trends, and time‐series models 461–2
truth tables:
and fuzzy‐set qualitative comparative analysis (fsQCA) 732
and qualitative comparative analysis 726–7
interpretation 729
limitations 730
Turing machines 282
typical cases, and case selection 648–50
typologies 8–9, 152–3, 166
and construction of 158
concept and term selection 159–61
concept formation 158–9
ideal vs classificatory types 161–2
and descriptive 153
and explanatory 153
and guidelines for working with 167–8
and structure of 153
basic template 153–6
cell types as categorical variables 156–7
collectively exhaustive categories 158
mutually exclusive categories 157
and uses of 162
comparative analysis 168
mapping empirical and theoretical change 163–5
quantitative analysis 165–6
structuring comparison 162–3
underdetermination thesis 712–13
unfolding analysis 204–5, 206, 208
unidimensional typologies 153 n2
unit homogeneity, and matching methods 272
vacancy chains, and individual actions 328
vaccination 301–2
validity:
and counterfactual statements 630–1
and experiments 343–4
and measurement 9, 120, 121–2
and types of 344 see also external validity
value change, and rise in causal thinking 6
variance, and measurement 122
variance decomposition 466
vector autoregression (VAR), and time‐series models 465–7
verification, and logical positivism 61
Vietnam War, and counterfactuals 640
voting:
and spatial model of 201, 207
and structural prediction 563–4
and theory testing of formal models 349–50 see also racial voting
war, and typology of 165–6
well‐being, and aggregation 99–100, 102
Western Political Quarterly 815
Wiley‐Wiley model, and measurement in dynamic setting 142–3
wishful thinking, and individual actions 326
women’s movements, and typologies 162
World Politics 790, 815
Yale Universit y 800
zero points:
and construction/evaluation of concepts and measures 103–5
and existence of 104
and interaction terms 105
and international conflict theory 103–4
and measurement theory 104–5