I. Seven Keys to Help You Avoid Errors and Reach Defensible Conclusions (Day I & 2)

Rule #1: Interpret Effects in the Context of Models

(1) Individual-level Example: Relative and absolute effects

G. Firebaugh and Laura Tach, “Income and Happiness in the United States,” unpublished manuscript.

(2) Macro-level Example: Does industrialization no longer benefit poor countries?

Giovanni Arrighi, Beverly J. Silver, and Benjamin D. Brewer. 2003. “Industrial Convergence, Globalization, and the Persistence of the North-South divide.” Studies in Comparative International Development 38:3-31.

G. Firebaugh. 2004. “Does Industrialization No Longer Benefit Poor Countries? A Comment on Arrighi, Silver, and Brewer, 2003.” Studies in Comparative International Development 39: 99-105.

Rule # 2. Consider all sources of error, not just sampling error

Rule # 3. To control for confounding factors in observational studies, try to supplement “control by regression” with techniques that mimic the effects of random assignment.

Liker, J., S. Augustyniak, and G. Duncan. 1985. "Panel data and Models of Change: A Comparison of First Difference and Conventional Two-Wave Models." Social Science Research 14:80-101.

Guang Guo, Leah K. VanWey. 1999. “Sibship Size and Intellectual Development: Is the Relationship Causal?” American Sociological Review (April 1999), 64: 169-187.

Meredith Phillips. 1999. “Sibship Size and Academic Achievement: What We Now Know and What We Still Need to Know.” American Sociological Review (April 1999), 64: 188-192.

Douglas B. Downey, Brian Powell, Lala Carr Steelman and Shana Pribesh. 1999. “Much Ado About Siblings: Change Models, Sibship Size, and Intellectual Development: Comments on Guang Guo & VanWey.” American Sociological Review (April 1999), 64: 193-198.

Guang Guo, Leah K. VanWey. 1999. “The Effect of Closely Spaced and Widely Spaced Sibship Size on Intellectual Development: Reply to Phillips and to Downey et al.” American Sociological Review (April 1999), 64: 199-206.