Main content

Wiki | References list by topic Discussion

References list by topic

Toggle view:
View
Compare

Menu

Project Wiki Pages
Component Wiki Pages
View
Wiki Version:

To suggest additional articles for this list, please go to the project main page and insert the citation as a comment (see the blue speech-bubble tab in the upper right corner). We will periodically add suggested papers to the main list, below.

I. RESEARCH METHODS

Experimental Design:

Collins, L.M., Dziak, J.J., & Li, R. (2009). Design of experiments with multiple independent variables: a resource management perspective on complete and reduced factorial designs. Psychological methods, 14(3), 202. Fulltext

Collins, L. M., Baker, T. B., Mermelstein, R. J., Piper, M. E., Jorenby, D. E., Smith, S. S., ... & Fiore, M. C. (2011). The multiphase optimization strategy for engineering effective tobacco use interventions. Annals of behavioral medicine,41(2), 208-226. Fulltext

Kover, S.T., & Atwood, A.K. (2013). Establishing equivalence: Methodological progress in group-matching design and analysis. American Journal of Intellectual and Developmental Disabilities, 118, 3-15. Link

Mervis, C.B., & Klein-Tasman, B.P. (2004). Methodological issues in group-matching designs: α levels for control variable comparisons and measurement characteristics of control and target variables. Journal of Autism and Developmental Disorders, 34, 7-17. Fulltext

General research methods:

Martin, J. (1980). A garbage can model of the research process. In J. E. McGrath, J. Martin, & R. A. Kulka, Judgment calls in research (pp. 17–39). Beverly Hills, CA. Link

Multilevel and/or Longitudinal Design:

Duncan, S. C., Duncan, T. E., & Hops, H. (1996). Analysis of longitudinal data within accelerated longitudinal designs. Psychological Methods, 1(3), 236. Link

Nye, B., Konstantopoulos, S., & Hedges, L. V. (2004). How large are teacher effects?. Educational evaluation and policy analysis, 26(3), 237-257. Fulltext

Philosophy of Science:

Mayo, D.G., & Spanos, A. (2006). Severe testing as a basic concept in a Neyman-Pearson philosophy of induction. British Journal of the Philosophy of Science, 57, 323-357. Fulltext

Power and Sample Size:

Bakker, M., van Dijk, A., & Wicherts, J.M. (2012). The rules of the game called psychological science. Perspectives on Psychological Science, 7, 543-554. Fulltext

Button, K.S., Ioannidis, J.P.A., Mokrysz, C., Nosek, B.A., Flint, J., Robinson, E.S.J., & Munafo, M.R. (2013). Power failure: Why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience, 14, 365-376. Fulltext

Killip, S., Mahfoud, Z., & Pearce, K. (2004). What is an intracluster correlation coefficient? Crucial concepts for primary care researchers. The Annals of Family Medicine, 2(3), 204-208. Fulltext

Maas, C. J., & Hox, J. J. (2005). Sufficient sample sizes for multilevel modeling.Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, 1(3), 86. Fulltext

Muthén, L. K., & Muthén, B. O. (2002). How to use a Monte Carlo study to decide on sample size and determine power. Structural Equation Modeling,9(4), 599-620. Fulltext

Spybrook, J., Raudenbush, S. W., Liu, X. F., Congdon, R., & Martínez, A. (2006). Optimal design for longitudinal and multilevel research: Documentation for the “Optimal Design” software. Survey Research Center of the Institute of Social Research at University of Michigan. Fulltext

Qualitative Methods:

Todd, Z., Nerlich, B., McKeown, S., & Clarke, D. D. (2004). Mixing Methods in Psychology: The Integration of Qualitative and Quantitative Methods in Theory and Practice. Psychology Press. Link

Replicable Science and Questionable Research Practices:

Brown, S. D., Furrow, D., Hill, D. F., Gable, J. C., Porter, L. P., & Jacobs, W. J. (2014). A Duty to Describe Better the Devil You Know Than the Devil You Don’t. Perspectives on Psychological Science, 9, 626-640. Link

Ellemers, N. (2013). Connecting the dots: Mobilizing theory to reveal the big picture in social psychology (and why we should do this). European Journal of Social Psychology, 43, 1-8. Link

Fuchs, H.M., Mirjam, J., & Fiedler, S. (2012). Psychologists are open to change, yet wary of rules. Perspectives on Psychological Science, 7, 639-642. Fulltext

John, L. K., Loewenstein, G., & Prelec, D. (2012). Measuring the prevalence of questionable research practices with incentives for truth telling. Psychological Science, 23, 524-532. Fulltext

Self- and Informant Report Methods:

Bartoshuk, L.M., Fast, K., & Snyder, D.J. (2005). Differences in our sensory worlds: Invalid comparisons with labeled scales. Current Directions in Psychological Science, 14, 122-125. Link

Vazire, S. (2006). Informant reports: A cheap, fast, and easy method for personality assessment. Journal of Research in Personality, 40, 472-481. Fulltext

Validity:

Brewer, M. B. (2000). Research design and issues of validity. Handbook of research methods in social and personality psychology, 3-16. Fulltext

Loevinger, J. (1957). Objective tests as instruments of psychological theory: Monograph Supplement 9. Psychological Reports, 3, 635-694. Link

II. DATA ANALYSIS

Uses and Misuses of Statistics:

Scarr, S. (1997). Rules of evidence: A larger context for the statistical debate. Psychological Science, 8, 16-17. Fulltext

Savalei, V., & Dunn, E. (2015). Is the call to abandon p-values the red herring of the replicability crisis?. Frontiers in Psychology, 6:245. Fulltext

Applied Problems:

Cramer, A. O., Sluis, S., Noordhof, A., Wichers, M., Geschwind, N., Aggen, S. H., ... & Borsboom, D. (2012). Dimensions of normal personality as networks in search of equilibrium: You can't like parties if you don't like people. European Journal of Personality, 26(4), 414-431. Fulltext

Hyde, J. S. (1994). Can meta-analysis make feminist transformations in psychology?. Psychology of Women Quarterly, 18, 451-462. Link

van de Leemput, I. A., Wichers, M., Cramer, A. O., Borsboom, D., Tuerlinckx, F., Kuppens, P., ... & Scheffer, M. (2014). Critical slowing down as early warning for the onset and termination of depression. Proceedings of the National Academy of Sciences, 111(1), 87-92. Fulltext

Vazire, S., & Gosling, S. D. (2004). e-Perceptions: personality impressions based on personal websites. Journal of personality and social psychology, 87(1), 123. Fulltext

Biological Psychology (neuro, geno):

Aarts, E., Verhage, M., Veenvliet, J. V., Dolan, C. V., & van der Sluis, S. (2014). A solution to dependency: using multilevel analysis to accommodate nested data. Nature neuroscience, 17(4), 491-496. Link

Allen, E. A., Erhardt, E. B., & Calhoun, V. D. (2012). Data visualization in the neurosciences: overcoming the curse of dimensionality. Neuron, 74(4), 603-608. Fulltext

Bassett, D. S., & Bullmore, E. D. (2006). Small-world brain networks. The neuroscientist, 12(6), 512-523. Fulltext

Erez, Y., Tischler, H., Moran, A., & Bar-Gad, I. (2010). Generalized framework for stimulus artifact removal. Journal of neuroscience methods, 191(1), 45-59. Fulltext

Franić, S., Dolan, C. V., Borsboom, D., Hudziak, J. J., van Beijsterveldt, C. E., & Boomsma, D. I. (2013). Can genetics help psychometrics? Improving dimensionality assessment through genetic factor modeling. Psychological methods, 18(3), 406. Fulltext

Logan, J. A., Petrill, S. A., Hart, S. A., Schatschneider, C., Thompson, L. A., Deater-Deckard, K., ... & Bartlett, C. (2012). Heritability across the distribution: An application of quantile regression. Behavior genetics, 42(2), 256-267. Fulltext

Medland, S. E., Neale, M. C., Eaves, L. J., & Neale, B. M. (2009). A note on the parameterization of Purcell’s G× E model for ordinal and binary data. Behavior genetics, 39(2), 220-229. Fulltext

Mills, K. L., & Tamnes, C. K. (2014). Methods and considerations for longitudinal structural brain imaging analysis across development. Developmental cognitive neuroscience, 9, 172-190. Link

Mumford, J. A. (2012). A power calculation guide for fMRI studies. Social cognitive and affective neuroscience, 7(6), 738-742. Fulltext

Mumford, J. A., & Poldrack, R. A. (2007). Modeling group fMRI data. Social cognitive and affective neuroscience, 2(3), 251-257. Fulltext

Yendiki, A., Koldewyn, K., Kakunoori, S., Kanwisher, N., & Fischl, B. (2013). Spurious group differences due to head motion in a diffusion MRI study. NeuroImage, 88, 79–90. Fulltext

Confidence Intervals:

Belia, S., Fidler, F., Williams, J., & Cumming, G. (2005). Researchers misunderstand confidence intervals and standard error bars. Psychological Methods, 10, 389-396. Fulltext

Fidler, F., & Loftus, G.R. (2009). Why figures with error bars should replace p values. Journal of Psychology, 217, 27-37. Fulltext

Dyadic data analysis:

Kashy, D. A., & Kenny, D. A. (2000). The analysis of data from dyads and groups. In H.T. Reis & C.M. Judd (Eds.), Handbook of research methods in social psychology (pp. 451-477). New York: Cambridge University Press. Link

Effect Size:

Chinn, S. (2000). A simple method for converting an odds ratio to effect size for use in meta-analysis. Statistics in medicine, 19(22), 3127-3131. Fulltext

Hill, C.J., Bloom, H.S., Black, A.R., & Lipsey, M.W. (2008). Empirical benchmarks for interpreting effect sizes in research. Child Development Perspectives, 2(3), 172-177. Fulltext

Latent Change Score Modeling:

Quinn, J. M., Wagner, R. K., Petscher, Y., & Lopez, D. (2014). Developmental Relations Between Vocabulary Knowledge and Reading Comprehension: A Latent Change Score Modeling Study. Child development.

Latent Class Analysis:

Nylund, K. L., Asparouhov, T., & Muthén, B. O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural equation modeling, 14(4), 535-569. Fulltext

Logistic Models:

Azen, R., & Traxel, N. (2009). Using dominance analysis to determine predictor importance in logistic regression. Journal of Educational and Behavioral Statistics, 34(3), 319-347. Fulltext

Chinn, S. (2000). A simple method for converting an odds ratio to effect size for use in meta-analysis. Statistics in medicine, 19(22), 3127-3131. Fulltext

O'Connell, A. A. (2006). Logistic regression models for ordinal response variables (Vol. 146). Thousand Oaks, California:: Sage Publications. Link

O'Connell, A. A., & McCoach, D. B. (Eds.). (2008). Multilevel modeling of educational data. IAP. Link

Peng, C. Y. J., Lee, K. L., & Ingersoll, G. M. (2002). An introduction to logistic regression analysis and reporting. The Journal of Educational Research, 96(1), 3-14. Fulltext

Yelland, L. N., Salter, A. B., Ryan, P., & Laurence, C. O. (2011). Adjusted intraclass correlation coefficients for binary data: methods and estimates from a cluster-randomized trial in primary care. Clinical Trials, 8(1), 48-58. Link

Longitudinal Analysis:

Collins, L. M., & Sayer, A. G. (2001). New methods for the analysis of change. American Psychological Association. Link

Hamaker, E. L., Nesselroade, J. R., & Molenaar, P. C. (2007). The integrated trait–state model. Journal of Research in Personality, 41(2), 295-315. Fulltext

Rabe-Hesketh, S., & Skrondal, A. (2008). Multilevel and longitudinal modeling using Stata. STATA press. Link

Meta-Analysis

Chan, M.E., & Arvey, R.D. (2012). Meta-analysis and the development of knowledge. Perspectives on Psychological Science, 7, 79-92. Fulltext

Davis‐Kean, P. E., & Sandler, H. M. (2001). A meta‐analysis of measures of self‐esteem for young children: A framework for future measures. Child development, 72(3), 887-906. Fulltext

Eagly, A. H., & Wood, W. (1994). Using research syntheses to plan future research. In H. M. Cooper & L. V. Hedges (Eds.), The handbook of research synthesis (pp. 485-500). New York: Russell Sage Foundation. Link

Smith, M. L., & Glass, G. V. (1977). Meta-analysis of psychotherapy outcome studies. American psychologist, 32, 752. Fulltext

Tsuji, S., Bergmann, C., & Cristia, A. (2014). Community-Augmented Meta-Analyses Toward Cumulative Data Assessment. Perspectives on Psychological Science, 9, 661-665. Link

Wood, W., & Eagly, A. H. (2009). Advantages of certainty and uncertainty. In H. Cooper, L. V. Hedges, & J. C. Valentine (Eds)., The handbook of research synthesis and meta-analysis (pp. 455-472). New York: Russell Sage. Link

Moderation and Mediation:

Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. London: Sage.

Frazier, P.A., Tix, A.P., & Barron, K.E. (2004). Testing moderator and mediator effects in counseling psychology research. Journal of Counseling Psychology, 51, 115-134. Fulltext

Kraemer, H. C., Kiernan, M., Essex, M., & Kupfer, D. J. (2008). How and why criteria defining moderators and mediators differ between the Baron & Kenny and MacArthur approaches. Health Psychology, 27, S101-108. Fulltext

Iacobucci, D., Saldanha, N., & Deng, X. (2007). A meditation on mediation: Evidence that structural equation models perform better than regressions. Journal of Consumer Psychology, 17, 140-154. Fulltext

Ledgerwood, A., & Shrout, P. E. (2011). The tradeoff between accuracy and precision in latent variable models of mediation processes. Journal of Personality and Social Psychology, 101, 1174-1188. Link

Valeri, L., & VanderWeele, T. J. (2013). Mediation analysis allowing for exposure–mediator interactions and causal interpretation: Theoretical assumptions and implementation with SAS and SPSS macros. Psychological methods, 18(2), 137. Fulltext

Multilevel Modeling:

Krull, J. L., & MacKinnon, D. P. (1999). Multilevel mediation modeling in group-based intervention studies. Evaluation Review, 23(4), 418-444. Fulltext

Krull, J. L., & MacKinnon, D. P. (2001). Multilevel modeling of individual and group level mediated effects. Multivariate behavioral research, 36(2), 249-277. Fulltext

McCoach, D. B., & Kaniskan, B. (2010). Using time-varying covariates in multilevel growth models. Frontiers in psychology, 1, 17. Fulltext

Singer, J. D. (1998). Using SAS PROC MIXED to fit multilevel models, hierarchical models, and individual growth models. Journal of educational and behavioral statistics, 23(4), 323-355. Fulltext

Yelland, L. N., Salter, A. B., Ryan, P., & Laurence, C. O. (2011). Adjusted intraclass correlation coefficients for binary data: methods and estimates from a cluster-randomized trial in primary care. Clinical Trials, 8(1), 48-58. Link

Multiple Regression:

Azen, R., & Budescu, D. V. (2003). The dominance analysis approach for comparing predictors in multiple regression. Psychological methods, 8(2), 129. Fulltext

Multivariate Statistics:

Tabachnik, B. G., & Fidell, L. S. (2012). Using multivariate statistics (6th ed.). Boston: Pearson.

Scale construction:

Clark, L. A., & Watson, D. (1995). Constructing validity: Basic issues in objective scale development. Psychological assessment, 7, 309 - 319. Fulltext

Structural Equation Modeling:

Ding, L., Velicer, W. F., & Harlow, L. L. (1995). Effects of estimation methods, number of indicators per factor, and improper solutions on structural equation modeling fit indices. Structural Equation Modeling: A Multidisciplinary Journal,2(2), 119-143. Fulltext

Rhemtulla, M., Brosseau-Liard, P. É., & Savalei, V. (2012). When can categorical variables be treated as continuous? A comparison of robust continuous and categorical SEM estimation methods under suboptimal conditions. Psychological methods, 17(3), 354. Fulltext

Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of psychological research online, 8(2), 23-74. Fulltext

Survival Analysis:

Singer, J. D., & Willett, J. B. (1993). It’s about time: Using discrete-time survival analysis to study duration and the timing of events. Journal of Educational and Behavioral Statistics, 18(2), 155-195. Fulltext

Test theory:

Crocker, L., & Algina, J. (1986). Introduction to classical and modern test theory. New York: Wadsworth.

Embretson, S. E., & Reise, S. P. (2013). Item response theory for psychologists. Psychology Press. Link

Publication culture

Ledgerwood, A., & Sherman, J.W. (2012). Short, sweet, and problematic? The rise of the short report in psychological science. Perspectives on Psychological Science, 7, 60-66. Link

Reporting Practices:

Franco, A., Malhotra, N., & Simonovits, G. (2014). Publication bias in the social sciences: Unlocking the file drawer. Science, 345, 1502-1505. Link

Franco, A., Simonovits, G. & Malhotra, N. (2015). Underreporting in political science survey experiments: Comparing questionnaires to published results. Political Analysis. Link

Kashy, D. A., Donnellan, M. B., Ackerman, R. A., & Russell, D. W. (2009). Reporting and interpreting research in PSPB: Practices, principles, and pragmatics. Personality and Social Psychology Bulletin, 35, 1131-1142. Fulltext

III. BLOGS ABOUT METHODS AND STATISTICS

Dorothy Bishop. BishopBlog.

Suzi Gage, Kate Button and others. Sifting the Evidence.

Jessica Hamrick.

Åse Kvist Innes-Ker. Åse Fixes Science.

Deborah Mayo. Error Statistics Philosophy.

Sophie Scott. Speaking Out.

Bobbie Spellman. My Perspectives (on PsychScience)

Simine Vazire. sometimes i'm wrong.

OSF does not support the use of Internet Explorer. For optimal performance, please switch to another browser.
Accept
This website relies on cookies to help provide a better user experience. By clicking Accept or continuing to use the site, you agree. For more information, see our Privacy Policy and information on cookie use.
Accept
×

Start managing your projects on the OSF today.

Free and easy to use, the Open Science Framework supports the entire research lifecycle: planning, execution, reporting, archiving, and discovery.