Texas Tech University

The Oxford Handbook of Quantitative Methods

oxford

Two volume set, available October, 2012

See the Oxford University Press Page for more information.

Included Chapters

Haig, B. D. The philosophy of quantitative methods.

Rosnow, R. L. & Rosenthal, R. Quantitative methods and ethics.

Widaman, K. F., Early, D. R., & Conger, R. D. Special populations.

Jaccard, J. Theory construction, model building, and model selection.

Harlow, L. Teaching quantitative psychology.

McDonald, R. P. Modern test theory.

De Ayala, R. J. The IRT tradition and its applications.

Spector, P. E. Survey design and measure development.

Kingston, N. M., & Kramer, L. B. High stakes test construction and test use.

Kelley, K. Effect size and sample size planning.

Hallberg, K., Wing, C., Wong, V., & Cook, T. D. Experimental design for causal inference: Clinical trials and regression discontinuity designs.

Steiner, P. M., & Cook, D. Matching and Propensity Scores.

Van Zandt, T., &Townsend, J. T. Designs for and analyses of response time experiments.

Ostrov, J. M., & Hart, E. J. Observational methods .

Bard, D. E., Rodgers, J. L., & Muller, K. E. A primer of epidemiology methods with applications in psychology.

Figueredo, A. J., Olderbak, S. G., & Schlomer, G. L. Program evaluation: Principles, procedures, and practices.

Yuan, K-H., & Schuster, C. Overview of statistical estimation methods.

Erceg-Hurn, D. M., Wilcox, R. R., & Keselman, H. H. Robust statistical estimation.

Kaplin, D. & Depaoli, S. Bayesian statistical methods.

Cavagnaro, D. R., Myung, J. I., & Pitt, M. A. Mathematical modeling.

Johnson, P. E. What would happen if...? Monte Carlo analysis in academic research.

Thompson, B. Overview of traditional/classical statistical approaches.

Coxe, S., West, S. G., & Aiken, L. S. Generalized linear models.

Woods, C. M. Categorical methods.

von Eye, A., Mun, E. U., Mair, P., & von Weber, S. Configural frequency analysis.

Buskirk, T. D., Tomazic, T. T., & Willoughbby, L. Nonparametric statistical techniques.

Greenacre, M. J. Correspondence analysis.

Anselin , L., Murry, A. T., & Rey, S. J. Spatial analysis.

Price, L. R. Analysis of imaging data.

Medland, S. E. Quantitative analysis of genes.

Ding, C. S. Multidimensional scaling.

Brown, T. A. Latent variable measurement models.

Hox, J. J., Multilevel regression and multilevel structural equation modeling .

McArdle, J. J. & Kadlec, K. M. Structural equation models.

MacKinnon, D. P., Kisbu-Sakarya, Y. & Gottschall, A. C. Developments in mediation analysis .

Marsh, H. W., Hau, K-T., Wen, Z & Nagengast, B. Moderation. .

Wu, W., Selig, J. P., & Little, T. D. Longitudinal data analysis.

Deboeck, P. R. Dynamical systems and models of continuous time.

Walls, T. A. Intensive longitudinal data.

Ram, N., Brose, A., & Molenaar, P. C. M. Dynamic factor analysis: Modeling person-specific process.

Wei. W. W. S. Time series analysis.

Peterson, T. Analyzing event history data.

Rupp, A. A. Clustering and classification.

Masyn, K. E. & Nylund-Gibson, K. Mixture modeling.

Beauchaine, T. P. Taxometrics.

Baraldi, A. N., & Enders, C. K. Missing data methods.

Donnellan, M. B., & Lucas, R. E. Secondary data analysis.

Strobl, C. Data mining.

Card, N. A. & Casper, D. M. Meta-analysis and quantitative research synthesis.

Wang, L. L., Watts, A. S., Anderson, R. A., & Little, T. D. Common fallacies in quantitative research methodology.