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# (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

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 insights into social processes 90

and institutional design 90–1

and nature of 78–9

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 time‐series models 469

Agreement, Method of 284

agreement theories 41

AIDS 312

Akaike's information criterion (AIC) 535

alliance dependence 714

American National Elections Studies (ANES) 386, 388

and feeling thermometers 205–20

and political efficacy 449

and response rate 391

American Psychological Association, and construct validity 122

*Annual Review of Political Science*790

anomalies 313

Arizona State University 789

aspirin 292–3

attributes, and agent‐based modeling 81

Australian Election Studies 386

autoregressive conditionally heteroskedastic (ARCH) model 464–5

average treatment effect (ATE) 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

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 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 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 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

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

bounds, and ecological inference 552–3

Box‐Jenkins approach, and time‐series models 463

Box‐Taio intervention model 464

British Election Studies 399

calibration 175–7, 197

and context‐setting conditions 176

and populations 176

and scope conditions 176

and set theory 174

and statistical interaction 176–7

campaign expenditure 406

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)
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 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 narrative choice:

convenience samples 762

‘good cases’ 761–2

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 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

case studies 26–7, 645

and clinical medicine 293

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

and qualitative comparative analysis 734

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

(p. 863)
and capacities 243

and counterfactuals 13, 220–1, 232–3, 290, 629

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 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

lawlike statements 230

and linguistic analysis of 223–4

and meaning of 223

and methodology 4

and Mill's methods 282, 283–4, 288

conditions 282

Indirect Method of Difference 287–8

Method of Agreement 284

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 psychological analysis of 221–3

and qualitative tools 23–6

and reasons as causes 65–6

and requirements of strong inferences 218

and rise in causal thinking 4–5, 30

agent‐based model of 6

behavioral revolution 6

experiments 16

invention of new tools 6

measurement of 7–12

qualitative approaches 24–6

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

centipede game 83

Centro de Investigación y Docencia Económicas (CIDE) 789

cholera 304–6

civil war onset:

and causes of 758–9

and incompleteness of statistical models 768–70

and statistical analysis of 759–60

CLARIFY 522

classificatory types, and typologies 161–2

Cochrane‐Orcutt 479

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 judgment, law of 201

*Comparative Political Studies*790

*Comparative Politics*790

comparative research:

and necessary conditions 724

(p. 864)
and set theory 724

and shared conditions 724

and shared outcomes 723–4

and specific connections 724–5

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 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

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

compliance, and Neyman‐Rubin‐Holland (NRH) theory 274

computational models 71–3

as agent‐based models 78–9

and requirements of 75

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

confirmation theory, and epistemology 56

consistent adjusted least squares (CALS) 134

Consortium on Qualitative Research Methods (CQRM) 28

content validity 121

contextual effects, and spatial interdependence 571

contractarianism 38–9

controls, and experiments 342

Cook's distance 658

cooperation, and surveys 390–1

coordination theories:

and rise in causal thinking 6

and shared‐value theories 43

and social theory 42–4

and spontaneous coordination 43–4

correlation matrix, and psychometrics 200–1

counterfactuals 641–2
(p. 865)

and causality 220–1, 232–3, 290, 629

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 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

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 interactions, and multilevel models 612–13

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

desires, and individual actions 326

desires, beliefs and opportunities (DBO) theory 326

developed countries, and calibrating degree of membership 194–6

direct method 186–90

indirect method 190–3

Deviance Information Criterion 506

Dickey‐Fuller tests 461

Difference, Indirect Method of 287–8

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 substitution patterns 524–7

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*469–70Duverger’s law 244

dynamic linear model (DLM), and measurement in dynamic setting 144–5

ecological inference 547, 564–6

and individual behavior 547

and mathematics of 548

and methodological practice 566

and models:

aggregated multinomial model 556–7

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 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 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

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 controversy over 830

and emphasis of 839–40

and evaluating models 840–1

and goal of approach 841

and initial use of 828

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

equilibria, and game theory 87–8

error correction models (ECMs), and time‐series 467–8

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 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

eugenics 199

event history, and time‐series cross‐sectional (TSCS) methods 487–9

Event Structure Analysis (ESA) 732

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 experimental data 341

and external validity 15

and field experiments 15, 357–8

attrition 372–3

classification of 359

definition of 358–9

growth and development of 359–62

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 need for theory in 351–2

and policy‐makers 353

in political science 339–40

and quasi‐experiments 239–40

and searching for facts 350–1

(p. 868)
explanation:

and asymmetrical nature of 65

and meaning holism 66–7

and rational choice theory 54

in social research 12–15

external forces, and survey methodology 397–8

extrapolation, and experiments 377–8

extreme points, and construction/evaluation of concepts and measures 105–6

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

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 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

fixed effects, and time‐series cross‐sectional (TSCS) methods 483

fluoridation 309–10

folk psychology 66

forecasting, and parametric models 541–2

free‐rider model 329

free‐riding, and interdependence 574

full information estimation 420–1

and legislative politics 424–5

and maximum likelihood 422–4

and three‐stage least squares 421–2

full maximum likelihood estimation (FMLE) 614

functional equivalence 109

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 relevant/irrelevant variation 183

and transforming interval‐scale variables 184–6

game theory 23, 45, 832

and Baron‐Ferejohn bargaining 76–8

and computational models, currency game 73–6

(p. 869)
and difference from agent‐based models 82–4

and equilibria 87–8

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

globalization, and interdependence 572

Granger causality 466

group‐level predictors, and multilevel models 611–12

Gulf War (1991) 713–14

hat matrix 658

hazard rate, and survival analysis 531

heteroskedastic probit model 524

hierarchical modeling 22

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

homogeneity, and construction/evaluation of concepts and measures 109–10

negative or zero cases 111–14

homoskedasticity 123

Huber‐White estimator 607

hypermethodologism 69

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

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

intentionality 65

interaction terms, and zero points 105

interest representation, and typology of 160

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 Typographical Union (ITU) 658

interpretation, and discrete choice methods 522

interpretativism 782–3

inter‐rater reliability 123–4

interstate rivalry, and aggregation problem 102

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

relativism 689–90

respondent dissembling 689

scientific status of data 688

strategic reconstruction 689

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

intraclass correlation, and multilevel models 607

intrapersonal variables, and survey methodology 398–400

invention, and rise in causal thinking 6

isomorphism 377

*Journal of Mixed Methods Research*791

*Journal of Theoretical Politics*790

Kalman Filter, and measurement in dynamic setting 144–5

Katrina, hurricane 343

Kwiatowski‐Phillips‐Schmidt‐Shin (KPSS) test 461

laboratory experiments 346–7

large‐n correlational analysis 26

latent response formulation, and structural equation models 444–5

latent variables 119, 120

and discrete choice methods 513

(p. 871)
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 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

level‐1 coefficients, and multilevel models 618–19

liberalization, and cross‐national diffusion 572

likelihood functions 504

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

lme4 (software package) 616

lung cancer 218

macro‐level outcomes, and mechanisms 329–32

major power status, and international conflict variables 101

marginal quasi‐likelihood (MQL) 617

Markov transition models, and time‐series cross‐sectional (TSCS) methods 490

matching methods 271–2, 277

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

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 concepts 7–8

and fuzzy‐set analysis as bridge between qualitative and quantitative approaches 182–3

and goals of 120–1

and multiple indicators 125

and reliability 120, 122–5

(p. 872)
inter‐item reliability 124

inter‐rater reliability 123–4

test‐retest reliability 123

and rise in causal thinking 7–12

and uses of 125–6

measurement models 119, 128

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 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 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 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 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 importance of 48

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

modifiable area unit problem (MAUP) 548

most different design 283

most similar design 283

moving average, and time‐series 460

*see also*autoregressive integrated moving average; autoregressive moving averageMoynihan Institute of Global Affairs 789

multidimensionality, and concepts 9–10

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 extensions of 615–17

and group‐level predictors 611–12

and intraclass correlation 607

and level‐1 coefficients 618–19

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

naive realism, and ontology 60–1

narratives:

and case studies 757–8

neighborhood model, and ecological inference 556

new institutionalism 53

newsletters, specialized 819–20

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

causal priority 253

counterfactual definition of causal effect 250

creation of mini‐possible worlds 250

identicality of counterfactual situations 250

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

ontological definition of causal effect based upon counterfactuals 251–3

origins of 273

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

opportunities, and individual actions 326

ordinary least squares (OLS), estimates 409–10

organizations:

and qualitative and multimethod research 783–90

paper and pencil surveys 386

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

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‐makers, and experiments 353

Political Action Data 448

*Political Behavior*339

political economy, and typology of 164

political efficacy, and structural equation models 448–51

political methodology:

and changes in field 29

and development of 808–10

and developments in political science 830–5

and functions of 3–4

political philosophy, and origins of 35

*Political Psychology*339

*Political Research Quarterly*790

political science:

and causality 4–5

pooling, and multilevel data 606–8

positivism 50

predictive validity 121

pre‐emption, and causality 241–2

Principal Component Analysis 200

probability:

and Bayesian approach 495

probit analysis 166

process tracing 25–6, 292

and affirmation of hypotheses 711

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 nature of 704

and nature of evidence 709–10

and provisional nature of 705

and theoretical explanation 704

and theory testing 704–5

and underdetermination thesis 712–13

and uses of 702

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

*Public Choice*339

*Public Opinion Quarterly*339

publishing 824–5

and changes in 824

and encyclopedias 822–3

and ‘missionaries’ or ‘theologians’ 824

and opportunities for 824–5

and publication bias 377

and qualitative and multimethod research 790–1

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 complex causation 725–6

and debates about 733

and dissemination of 734

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 specific connections 725

and temporality 732–3

and two‐step procedure 733

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

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 general methods 16–21

and mechanisms 324–5

and special topics 21–3

and statistical inference 324–5

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

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 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 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

regression analysis 6

and appeal of 24

and descriptive inference 17

and instrumental variables 19

and spurious relationships 18–19

relativity, and common measurement practices 178–9

reliability:

research design 276–7

Residues, Method of 288

respecification, and structural equation models 442–3

response functions 203–4

restricted maximum likelihood estimation (RMLE) 614

revolutionary perspectives 5

rules, and agent‐based modeling 81–2

sampling, and surveys 387–8

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

self‐fulfilling prophecy, and individual actions 328

shrink estimators 618

Simpson's Paradox 548

simulations, and experiments 343

skepticism 55

smallpox 301–2

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 social science methodology 5–6

sour‐grapes syndrome, and individual actions 326

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 error probit models 592–3

spatial interdependence 22–3, 598

and general theoretical model of 573–4

and institutional diffusion 571

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

spline functions 542

stability, and equilibria 87–8

Stable Unit Treatment Value Assumption (SUTVA) 15

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 multilevel models 451–2

structural prediction, and ecological inference 562–4

structure, and construction/evaluation of concepts and measures 98–103

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 methodology 385, 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

sampling 387–8

and measurement error 120–1

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 methodological practice 543

and questions addressed by 530

tax competition 574

test theory model 9

test‐retest reliability 123

tetrad difference 200

textbooks 823

*Theory and Society*790

theory evaluation 633

three‐stage least squares 421–2

tied data, and Cox models 539–40

time‐constant covariates (TCCs), and survival analysis 532

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

time‐series cross‐sectional (TSCS) methods 20–1

and applications 475

(p. 880)
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 rise in causal thinking 13

and spurious relationships 20

Time‐Sharing Experiments in the Social Sciences (TESS) 348

Tobler's Law 572

trade dependency, and international conflict variables 101–2

traditions, and meta‐methodology 49

training:

trends, and time‐series models 461–2

truth tables:

and fuzzy‐set qualitative comparative analysis (fsQCA) 732

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

underdetermination thesis 712–13

unit homogeneity, and matching methods 272

vacancy chains, and individual actions 328

vaccination 301–2

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 structural prediction 563–4

war, and typology of 165–6

*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

Yale Universit y 800