PPA 415 – Research Methods in Public Administration

1. PPA 415 – Research Methods in Public Administration Lecture 1 – Research Design

2. Language of Research • Key terms. • Theoretical – developing, testing, or exploring the ideas that social researchers have about the way the world operates. • Empirical – based on observations and measurements of reality. • Nomothetic – pertains to the general case rather than the individual.

3. Language of Research • Key terms (contd.) • Idiographic – focused on the individual rather than the general case. • Probabilistic – most social science relationships are based on tendencies or probabilities. • Causal – focused on cause-effect relationships to develop the capacity to predict or shape the world.

4. Types of Research Questions • Descriptive – Designed to describe what is going on or what exists. • Relational – Designed to look at the relationship between one more variables. • Causal – Designed to determine whether one or more variables causes or effects one or more outcome variables. • Research questions are cumulative.

5. Time Relationships • Cross-sectional – Measurements made at one point in time. • Longitudinal. • Repeated measures – two or three points in time. • Time series – multiple points in time.

6. Types of Relationships • Correlational – Establishes relationships between two or more variables. • Causal – Establishes that one or more variables causes or determines or more outcome variables. • Spurious – The difference between correlational and causal depends on the influence of third variables.

7. Variables • Variables are measurements that take different values for different cases. • Attribute – each value of a variable is known as an attribute, e.g., the variable gender has two attributes, male and female. • When examining the relationship between variables, the causal variable that influences is called the independent variable; the effect variables that is influenced is called the dependent variable. • The attributes of the variable must be exhaustive and mutually exclusive.

8. Hypothesis • A hypothesis states an explicit relationship between an independent and dependent variable: e.g., as levels of participation increase, voting turnout increases. • Alternative or research hypothesis: X causes Y. • Null hypothesis: X and Y have no relationship. • In research, you test the probability of no relationship or no effect.

9. Type of data • Qualitative – measured with labels or categories. • Quantitative – measured with numbers. • The distinction is usually academic.

10. Unit of Analysis • Depends on the research question. • Individuals. • Groups. • Artifacts. • Geographical units.

11. Research Fallacies • Ecological fallacy. • Drawing conclusions about individuals on the basis of groups or aggregations. • Exception fallacy. • Making generalizations about groups or aggregations on the basis of individuals.

12. Research Process • Begin with broad questions. • Narrow down, focus in. • Operationalize. • Observe. • Analyze data. • Reach conclusions. • Generalize back to questions.

13. Research Stages • Research problem. • Research question. • Program (cause). • Units. • Outcomes (effect). • Design.

14. Validity Model

15. Types of Validity

16. Statistics • Descriptive – (1) when the researcher needs to summarize or describe the distribution of a single variable (data reduction) and (2) when the researcher wishes to understand the relationship between two or more variables (association). • Inferential – when the researcher wants to generalize findings from a sample to a population.

17. Variables • Discrete – a variable is discrete variable if it has a basic unit of measurement than cannot be subdivided. • Continuous – a variable is continuous if the measurement of it can be subdivided infinitely.

18. Levels of Measurement • Nominal level of measurement – Places cases in categories • Ordinal level of measurement – Places categories in order of more or less. • Interval level of measurement – Uses a unit of measurement. • Ratio level of measurement – Has a substantive zero point.

19. Edward Tufte’s Principles of Quantitative Reasoning • Documenting the sources and characteristics of the data. • Insistently enforcing appropriate comparisons. • Demonstrating mechanisms of cause and effect.

20. Edward Tufte’s Principles of Quantitative Reasoning • Expressing those mechanisms quantitatively. • Recognizing the inherently multivariate nature of analytic problems. • Inspecting and evaluating alternative explanations.