Qualitative vs. Quantitative Research - 1 Qualitative and quantitative studies are both types of observational studies. Quantitative research measures differences in number for variables, and usually studies a large number of cases (Large “N”). Qualitative research measures differences in kind for variables, and usually studies a small number of cases (Small “N”).

Qualitative vs. Quantitative Research - 2 Because it covers a broad range of cases, quantitative research yields conclusions that can be generalized more widely (it has the strongest external validity). Because it looks closely at a few cases and traces causal pathways, qualitative research outperforms quantitative research in its measurement validity and internal validity (Do the independent variables effect the dependent variable?)

Qualitative vs. Quantitative Research - 3 When selecting cases for your quantitative research sample, it is imperative that you use random selection. In qualitative research, “selection must be done in an intentional fashion, consistent with research objectives and strategy.”

Selecting Cases on the Independent Variable - 1 “Selecting on the independent variable” means “selecting your cases according to the values of the independent variable that they take on.” In order to do this, you have to know a little bit about all of your potential cases. In order to do this right, you CANNOT act as if you also know the values that the dependent variable takes on.

Selecting Cases on the Independent Variable - 2 The Most Similar Systems method selects cases that take on similar values of confounding variables, but different values of a key independent variable. This “holds constant” the confounds because they take on the SAME values in all of the cases.

Selecting Cases on the Independent Variable - 3 The cases that you might select in a Most Similar Systems design will differ based on the research question you ask. For example, Bill Clinton, Jimmy Carter and Barack Obama for the impact of region on voting (since all are Democrats you’ve “controlled” for political party – not all three are from the same region so region “varies” – however, since region and race vary together, race could be a “confound”).

Selecting Cases on the Independent Variable - 4 The Most Different Systems method selects cases that take on very different values for multiple independent variables. If it turns out that these cases all take on the same value of a dependent variable, then we can rule out the independent variables as causes of the dependent variable. Such a situation would mean that we could only disprove a hypothesis. That’s why we typically avoid this method.

Income Inequality and Civil War Poverty Civil War Colonial Past External Threat

Income Inequality and Civil War Case Income Inequality Poverty Colonial Past External Threat Costa Rica Moderate Yes Yup Nope El Salvador High Cuba

Income Inequality and Civil War Case Civil War? Costa Rica No El Salvador Yes Cuba We can hold the confounds constant by selecting these similar cases from Latin America. It appears that income inequality does lead to civil war.

Selecting on the Dependent Variable - 1 Selecting cases according to the value of the dependent variable that they take on is more controversial than selecting on the independent variable. It is crucial to select observations WITHOUT regard to values of the independent variables.

Selecting on the Dependent Variable – 2 When you use Mills’ Method of Agreement, you select cases that take on the SAME values of the dependent variable. This helps you to rule out possible causes, because independent variables that vary over these cases CAN’T cause the dependent var. This method can only DISPROVE a hypothesis, because it can’t find a correlation.

Selecting on the Dependent Variable - 3 This design could help us rule out “early industrialization” as a cause of whether a country has a viable socialist party. Case Early Industrialization? Viable Socialist Party? France No Yes Britain

Selecting on the Dependent Variable - 4 When you use Mills’ Method of Difference, you select cases that take on DIFFERENT values of the dependent variable. After you have selected your cases, you determine what values they take on for some independent variables. Perhaps one independent variable will vary across your cases, and explain the D.V.

Selecting on the Dependent Variable - 5 Adding a country that has no viable socialist party can add causal leverage to our early investigation. Case Early Indust.? Feudalism? Viable Social Party? France No Yes Britain USA

Comparing Many Research Methods: Measurement Validity Measurement validity judges the gap between your conceptual definition and your operational definition. Qualitative – Highest measurement validity The measurement validity of other research methods (Lab experiments, quasi/natural experiments, and quantitative research) really depends on what you are trying to measure.

Comparing Many Research Methods: Internal Validity Internal validity judges how well a research design has tested a causal relationship, in the cases examined. Random assignment is the key. Lab Experiments – highest Quasi/Natural experiments – medium Qualitative research – medium Quantitative research – lowest

Comparing Many Research Methods: External Validity External validity is how confident we can be that a causal relationship identified in our cases can be generalized to the outside world. Random sampling is key Quantitative research – highest Quasi/Natural experiments – medium Lab experiments – low Qualitative research – low

Comparing Many Research Methods: Overall Lessons The best research design depends on your research question and the particular problems that it poses. The best research uses a mixture of methods to test a hypothesis.