The research paper

1. The research paper

2. Approaches • Find data, think of question + hypothesis. • Hypothesis must have theoretical justification. • Question + hypothesis, try to find data. • Theoretical relationship not yet tested • If you do compile a dataset  Remember to collect data for: DV, main IV of interest, and also control variables (theoretically driven). • Bwght = cigs • Bwght = cigs + faminc + mothereduc + fathereduc

3. Data Potential data sources • World Handbook of Political and Social Indicators: country measures of inequality, GDP, political events, executive changes, imports, exports, for 155 countries. • World Bank; Human Development Index, Human Poverty Index;; Author websites; Uppsala conflict database; PRIO; Polity; Freedom House; Eurobarometer; Journal replication websites – JPR, JCR Potential problems: • Data is in a non-SPSS format. E.g. stata (.dta) format. • Lots of missing values. (Pairwise versus listwise deletion)

4. Data • Also remember: • There are many different regression models. The regression model you use will be contingent on the type of data you have. • For linear regression – scale DV, scale or binary (dummy) IVs, cross-sectional data • For time series regression – panel data • For logit or probit regression – nominal or ordinal DV

5. Structure • General introduction. • What is the research question? • Literature review • Enough to provide some context. What are the gaps in current knowledge and where does your research fit? • Theoretical framework and hypotheses • This can follow directly from your literature review. Perhaps one hypothesis and an alternative hypothesis.

6. Structure • Operationalization of variables • This section should show how the theory translates into empirics. (How are your concepts measured). • What is the DV, the main IV of interest, what are the control variables. • For each, say how they are measured (nominal, ordinal, scale), and the source of the data. • Justify the choice of regression model.

7. Structure • Empirical Analysis • Report the regression results. Include a regression table and interpret the results both substantively and statistically. • You should: Get to know your data – examine single variables. Look at the relationship between variables - scatterplots, crosstabs. Check your data for outliers (z-scores) Check your model for problems (multicollinearity and heteroskedasticity). • But you shouldn’t: report every single step.

8. Structure • Conclusion • Reiterate the main findings. • Talk about the reliability of the analysis. • If there were problems with your variables – say that the results must be treated with caution.

9. Miscellaneous • Include an appendix containing descriptive statistics (at a minimum for your DV and main IV). • Always put the number of cases at the bottom of a regression table (n = 147). • It’s good practice to state the number of missing values (even for crosstabs!). • There’s no need to include both values and labels (for e.g. most likely to vote (3)). • Technical details and vocabulary related to SPSS should be removed.

10. The End. • Good luck. • I’m sure you’ll do fabulously. • Any questions? • Has anyone found any good data yet?