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Epistemology and Methods Small-N and Large-N Studies May 12 2009

Epistemology and Methods Small-N and Large-N Studies May 12 2009. Conflict vs. co-existence. Methods are used to test theories or assist in theory-building Quantitative or quantitative methods have different strengths and weaknesses Different “group think” attitudes have led to sharp divisions

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Epistemology and Methods Small-N and Large-N Studies May 12 2009

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  1. Epistemology and MethodsSmall-N and Large-N StudiesMay 12 2009

  2. Conflict vs. co-existence • Methods are used to test theories or assist in theory-building • Quantitative or quantitative methods have different strengths and weaknesses • Different “group think” attitudes have led to sharp divisions • Common quest, different routes…

  3. Qualitative methods: what is this? Other “label”: case study methods (single case design or comparison of cases) • Mostly used qualitative method is: • Process-tracing • Whether intervening variables between a hypothesized cause and observed effect move as predicted by theories… • Also used, albeit less frequently, is: • Counterfactual analysis • Whether x in a specified case was necessary for y…

  4. Case study design Forms of single case study design • Descriptive case study Written by participants or historians • Preliminary illustration of a theory Keohane (1984) on the role of regimes

  5. Case study design 3) Disciplined interpretative case study • Interpretation/explanation of an event by applying a known theory • Could lead to improvement of theory • Risk: underplaying evidence inconsistent with the argument, eclectic approach (which factors are more important) • Remedy: Engage sincerely in alternative explanations, add counterfactual arguments

  6. Case study design • Hypothesis-generating case study • Schattschneider (1935) Politics, Pressures, and the Tariff Literature on pressure group politics • Kindleberger (1973): “that for the world economy to be stabilized, there has to be a stabilizer, one stabilizer“

  7. Case study design 5) Least-likely (theory-confirming) case study • Extreme case that is highly unlikely to confirm • Lends strong support if confirmed • Example: The WTO treaties constrain actor’s national policies – case-study on the US

  8. Case study design 6) Most-likely (theory-infirming) case study • An important single case study that disconfirms the expected outcome even though conditions make the case favorable for theory • Example: The WTO dispute settlement system is biased against developing countries – case-study on Benin’s application and success rate…

  9. Case study design • Deviant case study (outlier cases) • Shedding light on the limits of a theory • Suggesting new hypotheses • Japan’s attack on Pearl Harbor and Deterrence Theory (Russett 1967)

  10. Comparative methods • (Mill’s Methods and Least-Similar and Most-Similar Case Comparisons) • The method of agreement (least similar case design) • Search for similar antecedent conditions / ideally necessary conditions • E.g. negotiations in GATT vs. WTO (A: G2 power)

  11. Comparative methods • The method of difference (most similar case design) • Method of controlled comparison • BCDE (constant) • E.g. disputes on similar cases: GATT vs. WTO (A: modified dispute settlement system)

  12. Discussion Advantages of case studies • Generate valid theory • Refining theory, generate new hypotheses • Strong for documenting processes /making inference regarding causal mechanisms • Finding omitted variables • Key events better explained than in large-n statistical tests…

  13. Discussion Limits of case studies • Less useful for systematic testing a theory • Case selection bias • Confirmation bias • Potential indeterminacy • Representativeness (generalizability vs. specificity) • Lesser precision of magnitude of causal effects

  14. Quantitative methods What is statistical method capable of doing? • Short-cut: “it permits the researcher to draw inferences about reality based on the data at hand and the laws of probability” • From descriptive statistics to inferential statistics

  15. Discussion Advantages: • Powerful tool to “aggregate information” from a large amount of data • Clear transparent coding process (high reliability, possibility for replication) • Visual display • Test whether association between variables is a product of chance

  16. Discussion Advantages: • Measure the effect of a change on the IV on the DV • Assess the “contribution” (explanatory power) of an IV (average explanatory effects) • Mapping of “deviant cases” • Generalizability

  17. Discussion Limits: • Identifying new variables • Dealing with multiple conjunctural causality or equifinality • Validity of operationalization of variables • Role of important cases

  18. Discussion Errors of Specification: • Too much effort calculating correlations with little attention to theory (i.e. democratic peace) • Theory itself often imprecise/shallow – does not lend itself to be tested (i.e. Waltzian balancing vs. bandwagoning) • Imposing a statistical model on the theory (inattention to causal processes...)

  19. Discussion Errors of Inference: • Focus on statistical significance (probability that relationship between A and B occurred by chance) vs. substantive significance (magnitude of the relationship) • Mining datasets /few non-results make it to publication

  20. Summing up (Mahoney and Goertz 2006)

  21. Summing up (Mahoney and Goertz 2006)

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