Articles

This page will have articles specifically for class and others that will be beneficial to your research efforts in general and will also help you learn the material, but which are not required reading. All assigned readings will also be found in the Related Readings section. At the bottom is a selected bibliography of texts that I have used in developing my courses in both alphabetical form and by topic..

Readings for class	Related Readings
5700 Haack 1996: Concern for truth Rosnow & Rosenthal Chapter 1, 2, 3 Wilkinson, 1999: APA task force guidelines Wright 2003: Making friends with your data Cohen 1990: Things I have learned so far... Cohen 1994: The earth is round, p < .05 Cohen 1992: Power and Effect Size Thompson 2002 Tryon: Inferential Confidence Intervals Streiner 2004: Unicorns do exist Wilcox: Psychology's Weak Link See also: How many discoveries lost (AmerPsych 1998) in Modern Approaches to the right, and this. 5710 Recent Amer Psyc article Wilcox chapter handout OR Wilcox (2001): Modern Insights regarding correlation Howell chapter 9 and 10 for review Howell Chapter 15 Howell Chapters11-14 Kline Chapters 6,7 Supplemental Readings Howell chapter 16 Moderation and Mediation classic, Baron & Kenny (1986) Sums of Squares Solomon 4-group design, Braver & Braver 1988 Reliability and Power, Zimmerman & Williams 1986 Subject by treatment interaction, Lyons & Howard 1991 6810 The Modern Approach Recent Amer Psyc article Regression Howell: Chapter 15 MR (handout) Wilcox: Robust correlation and regression (handouts) Harrell: Validation (handout) Assumptions to Always Test in Regression (Osborne & Waters) Moderation/Mediation supplemental Mediators, Moderators, and Tests for Mediation (James & Brett 1984) Basic problems in interaction assessment (Greenland 1993) Testing Moderator and Mediator Effects in Counseling Psychology (Frazier et al. 2004) When Moderation Is Mediated and Mediation Is Moderated (Muller, Judd, Yzerbyt 2005) Direct and Indirect Effects (Pearl 2001) Comparison of Moderation, Confounding, Mediation (MacKinnon et al.) Mediation Analysis (Mackinnon et al. 2007) Clinical setting (Holmbeck 1997) Multilevel Modeling (Bauer, Preacher, Gil 2006) Addressing Moderated Mediation Hypotheses (Preacher et al. 2007 Integrating Moderators and Mediators (Edwards & Lambert, 2007) Quantile Regression supplemental Gentle introduction (Cade & Noon, 2003) Basics (Koenker & Hallock, 2001) Bayesian Model Averaging supplemental Tutorial (Hoeting et al. 1999) BMA in action GLM supplemental Cohen classic Principal Components Analysis Lattin Carrol and Green handout PCA in action (supplemental) Canoncial Correlation Thomspon Primer Cancorr in action (supplemental) Partial Least Squares supplemental From the folks at SAS MANOVA Tabachnick and Fidell Handout MANOVA in action (supplemental) CLASSIFICATION Multiple handouts Classification in action (supplemental) PATH ANALYSIS Keith handout Path Analysis in Action, #2 (supplemental) FACTOR ANALYSIS Factor Analysis, Darlington Factor Analysis in Action (supplemental)	Science General Overcoming Veriphobia (Bailey) Popper, Fisher, Bayes Relativism (SEP) Science: Conjectures and Refutations (Popper) Investigating fraud in scientific research Stats and Psychological Science (Rosnow) Our Faith in Science (Tenzin Gyatso) Haack 1996: Concern for truth Rosnow & Rosenthal Chapter 1, 2, 3 Myths and Legends in Quantitative Psychology (Grayson) NHST APA task force guidelines The fallacy of the null hypothesis significance test (Rozeboom) P-values are not error probabilities (Hubard & Bayarri) Even stats guys misinterpret NHST (Lecoutre et al.) Things I have learned so far... (Cohen) The earth is round, p < .05 (Cohen) The problem is epistemology not statistics (Meehl) Down with statistical rituals! (Gigerenzer) Krantz, NHST controversy Fisher <3 Bayes?? (Aldrich) Summary (me) The difference between “significant” and “not significant” is not itself statistically significant (Gelman & Stern) Data Exploration Initial Data Analysis (Chatfield) Biases in research interpretation (MacCoun) The normal unicorn (Micerri) The median is not the message (Gould) Avoiding statistical pitfalls (Chatfield) Missing Data (Enders) (Roth) Measures of Central Tendency (Streiner) CIs, ICIs, Equivalence Inferential Confidence Intervals, 2 (Tryon) Equivalence Testing (Rogers,Howard, Vessey) Equivalence testing (Yours truly) Graphical CIs (Masson & Loftus) Unicorns do exist (Streiner) Effect size Effect sizes compared (Rosnow & Rosenthal) More effect size (Olejnik and Algina) Power and Effect Size (Cohen) Small effect sizes, practical importance (Prentice & Miller) When a little is a lot (Abelson) CIs for effect size (Thompson) One more about small effects and practical importance (Rutledge and Loh) Beyond the F test (Steiger) ANOVA False Discovery Rate (Benjamini & Hochberg) Multiple comparisons compared 1,2 Bluffer's guide to sphericity (Field) Reader Questions involving Anova (J of Consumer Psyc) Dealing with Heterogeneity of Variance (Bryk & Raudenbush) Regression Why you should not categorize continuous variables (Harrell) The moderator-mediator variable distinction. (Baron & Kenny). Comparison of Moderation, Confounding, Mediation (MacKinnon et al.) Classic on the General Linear Model (Cohen) Multivariate specific Handout regarding IDA for the multivariate situation Canonical Correlation Primer (Thompson) My Canonical Correlation article Multivariate Effect Size Estimation (Kline supplemental) Exploratory Factor Analysis book (Tucker & MacCallum) History of Exploratory Factor Analysis (Mulaik) Cluster Analysis (me; very intro. I was still a student and had not taught multivariate) Path Analysis Intro (Streiner) Modern approaches How many discoveries lost? (Wilcox) Wilcox 2: Resistant Boogaloo (Erceg-Hurn & Mirosevich) Psychology's Weak Link (Wilcox) Modern Insights regarding correlation (Wilcox) Herrington: Robust Measures of Location, Robust effect size, Estimating Power with the Bootstrap Bootstapping Cohen's d (Kelley) Resampling methods Several dozen applications of modern approaches Applied use of modern methods These are big files (even zipped) containing many articles (about 70 not counting the methods) so if you want to download in parts or whole it's up to you. Everything. Robust examples. Equivalence Testing examples. Methods articles. Description.
Selected Bibliography Ableson, R.P. (1995). Statistics as principled argument. Aiken & West (1991). Multiple regression: testing and interpreting interactions. Bartholomew et al. (2002). The analysis and interpretation of multivariate data for social scientists. Berry, D. (1995). Statistics: A Bayesian Perspective. Bernstein (1988). Applied multivariate analysis. Bray & Maxwell (1985). Multivariate analysis of variance. Bryk, A. S. & Raudenbush, S. W. (1992): Hierarchical Linear Models. Carroll & Green (1997). Mathematical tools for applied multivariate analysis. Chalmers, A.F. (1976). What is this thing called science? Cohen, J. (1988). Statistical Power Analyses for the Behavioral Sciences. Cohen & Cohen (1983). Applied regression analysis for the Behavioral Sciences Dunteman, G. (1989). Principal components analysis. Fox, J. (1997). Applied Regression Analysis, Linear Models, and Related Methods. Gelman & Hill (2007). Data Analysis Using Regression and Multilevel/ Hierarchical Models Gill, J. (2006). Essential Mathematics for Political and Social Research. Hastie, Tibshirani, & Friedman (2001). Elements of Statistical Learning. Harrell, F. (2001). Regression modeling strategies. Harlow, L. (1999). What if there were no significance tests? (Ed). Harlow (2005). The essence of multivariate thinking. Howell, D. (2007). Statistical Methods for Psychology. Keith, T. Z. (2005). Multiple regression and beyond. Keppel, G. (2004). Design and Analysis. Keren & Lewis (Eds.) (1993), A Handbook for Data Analysis in the Behavioral Sciences: Methodological Issues. Kim & Mueller (1978). Introduction to factor analysis: What it is and how to do it. Kim & Mueller (1978). Factor analysis: Statistical methods and practical issues. Kirk (1995). Experimental design. Klecka (1980). Discriminant analysis. Kline, R. (2004). Beyond significance testing. Kline (2005). Principles and practice of structural equation modeling. Kourany, J.A. (1987). Scientific knowledge. Kreft & de Leuuw (1998). Introducing Multilevel Modeling Lattin, Carroll, and Green (2003). Analyzing Multivariate Data. Laudan, L (1990). Science and relativism. Maxwell & Delaney. (1990). Designing experiments and analyzing data. Menard, S.(1995). Applied Logistic Regression McDonald (1999). Test theory: A unified treatment. McDonald (1985). Factor analysis and related methods. Pampel, F. (2000). Logistic Regression: A Primer. Pedhazur, E. (1997).Multiple Regression in Behavioral Research Rutherford, A. (2001). Introducing ANOVA and ANCOVA, a GLM approach. Stevens (multiple editions). Applied multivariate statistics for the social sciences. Rosnow, R, & Rosenthal (1991). Essentials of Behavioral Research. Rosnow, R, & Rosenthal, R (2003). Effect Sizes for Experimenting Psychologists. Tabachnick & Fidell (2006). Using multivariate statistics. Tastuoka (1971). Multivariate analysis Thompson (1984). Canonical correlation analysis: Uses and interpretation. Thompson (1991). A primer on the logic and use of canonical correlation analysis. Thompson, B. (2004). Exploratory and Confirmatory Factor Analysis Wilcox, R. (2003). Applying Contemporary Statistical Techniques Wilcox, R. (2002). Fundamentals of Modern Statistical Methods: Substantially Improving Power and Accuracy Wilcox, R. (1997). Introduction to Robust Estimation and Hypothesis Testing Winer (1991). Statistical principles in experimental design. By category Intro Ableson, R.P. (1995). Statistics as principled argument. Chalmers, A.F. (1976). What is this thing called science? Howell, D. (2007). Statistical Methods for Psychology. Kourany, J.A. (1987). Scientific knowledge. Laudan, L (1990). Science and relativism. Research Design Cohen, J. (1988). Statistical Power Analyses for the Behavioral Sciences. Keppel, G. (2004). Design and Analysis. Kirk (1995). Experimental design. Maxwell & Delaney. (1990). Designing experiments and analyzing data. Rutherford, A. (2001). Introducing ANOVA and ANCOVA, a GLM approach. Rosnow, R, & Rosenthal (1991). Essentials of Behavioral Research. Winer (1991). Statistical principles in experimental design. Null Hypothesis Testing Harlow, L. (1999). What if there were no significance tests? (Ed). Keren & Lewis (1993), A Handbook for Data Analysis in the Behavioral Sciences: Methodological Issues. (Ed.) Kline, R. (2004). Beyond significance testing. Mutliple Regression Aiken & West (1991). Multiple regression: testing and interpreting interactions. Fox, J. (1997). Applied Regression Analysis, Linear Models, and Related Methods. Cohen & Cohen (1983). Applied regression analysis for the Behavioral Sciences Harrell, F. (2001). Regression modeling strategies. Keith, T. Z. (2005). Multiple regression and beyond. Menard, S.(1995). Applied Logistic Regression Pampel, F. (2000). Logistic Regression: A Primer. Pedhazur, E. (1997).Multiple Regression in Behavioral Research. Multivariate (general) Bartholomew et al (2002). The analysis and interpretation of multivariate data for social scientists. Bernstein (1988). Applied multivariate analysis. Bray & Maxwell (1985). Multivariate analysis of variance. Carroll & Green (1997). Mathematical tools for applied multivariate analysis. Gill, J. (2006). Essential Mathematics for Political and Social Research. Harlow (2005). The essence of multivariate thinking. Lattin, Carroll, and Green (2003). Analyzing Multivariate Data. Stevens (multiple editions). Applied multivariate statistics for the social sciences. Tabachnick & Fidell (2006). Using multivariate statistics. Tastuoka (1971). Multivariate analysis Multivariate (specific) Bryk, A. S. & Raudenbush, S. W. (1992): Hierarchical Linear Models. Dunteman, G. (1989). Principal components analysis. Gelman & Hill (2007). Data Analysis Using Regression and Multilevel/ Hierarchical Models Kim & Mueller (1978). Introduction to factor analysis: What it is and how to do it. Kim & Mueller (1978). Factor analysis: Statistical methods and practical issues. Klecka (1980). Discriminant analysis. Kreft & de Leeuw (1998). Introducing Multilevel Modeling Kline, R. (2005). Principles and practice of structural equation modeling. McDonald, R. (1999). Test theory: A unified treatment. McDonald, R. (1985). Factor analysis and related methods. Thompson, B. (2004). Exploratory and Confirmatory Factor Analysis Thompson, B. (1984). Canonical correlation analysis: Uses and interpretation. Modern approaches Berry, D. (1995). Statistics: A Bayesian Perspective. Hastie, Tibshirani, & Friedman (2001). Elements of Statistical Learning. Wilcox, R. (2003). Applying Contemporary Statistical Techniques. Wilcox, R. (2002). Fundamentals of Modern Statistical Methods: Substantially Improving Power and Accuracy. Wilcox, R. (1997). Introduction to Robust Estimation and Hypothesis Testing.