Instructor: Adam Winsler, Ph.D. Office: 2011 David King Hall

Phone: (703) 993-1881 Office Hours: Tues 11-12, Thurs 2-3, + by appt.

Course Schedule T R 3:00 -4:15pm Location: Science & Tech. 1 Rm. 131

Credit Hours: 4

Kara Incalcaterra Karin Orvis Louis Manfra

Lab Section 612 205 Lab Section 612 211 Lab Section 612 209

Friday 8:30-10:20 Thurs 5:00-6:50 Thurs 5:00-6:50

DK 1005 **Thompson 222** DK 1005

Lab Section 612 206 Lab Section 612 207 Lab Section 612 210

Friday 10:30-12:20 Friday 12:30-2:20 Thurs 7:00-8:50

DK 1005 DK 1005 DK 1005

Office Hours: Office Hours: Office Hours:

Tues 2-3 Thurs 2-3 Wed 1-2

Robinson B211 Robinson B213 DK 2057

(703) 993-3706 x1 (703) 993-3706 x4 (703) 993-4050

This course is designed to a) sensitively initiate students into the authentic activities that make up the culture of applied data analysis in psychology, and b) to increase students’ knowledge and skills as consumers of research and statistics. No matter what students' career tracks are, they will almost certainly be called upon at some point to either understand the findings of research to improve applied practice, analyze a set of data either for local institutional purposes or for academic publication purposes, conduct an empirical investigation, or evaluate a program of research or service. So the goal of this course is to help prepare students for these tasks. As everyone always says, the best way to learn statistics is by doing them, so we will be "doing them" as authentically as possible with the same, processes, tools, and procedures that are used in the field. Through a combination of lecture, discussion, presentation, projects, homeworks, and other activities, we will significantly increase (p < .05) student knowledge and skill with regard to research methods and statistics, and inform students what else there is that they might want to learn in this area and where to go to learn it.

1) Howell, D. C. (1997). Statistical methods for psychology (4th ed.). Belmont, CA: Wadsworth.

2) Kerlinger, F. N., & Lee, H. B. (2000). Foundations of behavioral research (4th ed.). Fort Worth, TX: Harcourt.

3. Selected articles (see list below) on electronic (journal articles) and hard copy (book chapters) reserve at JC library. (Because it will take a few days for this to be up, the first 3 articles are also available at the course website.

2) Carver, R.H., & Nash, J.G. (2000). Doing data analysis with SPSS 10.0. Pacific Grove, CA: Brooks/Cole.

Students are encouraged to submit as many additional items as they want since it is a good learning experience and all students benefit by studying via the on-line study guide. Students can earn up to 5 final exam extra credit points (1 point for each additional good item submitted) by submitting additional items at any time to the on-line study guide. However, you don’t the get XC points until after you have completed your required 5.

Note: This semester, we will be using a newer version of WebCT. Most all features are used the same way, but look better and slightly different. The largest difference is the way in which you log in. In this version, you will log into your own individual MyWebCT account, and from there access the 612 WebCT page. To do this, simply locate the URL above in any browser, click on LOG ON TO MYWEBCT, and enter your mason user account (the first part of your mason email address, e.g. jsmith5) as your login ID, and the last four digits of your social security number as your password. IF YOU ARE NOT ABLE TO ACCESS YOUR MYWEBCT ACCOUNT, THEN YOU ARE NOT IN THE CURRENT REGISTRAR'S DATABASE AS ENROLLED IN ANY CLASSES.

The standard 93-100% = A, 90-92 = A-, 87-89% = B+, 83-86 = B, 80-82 = B-, 77-79% = C+, 70-76 = C, 60-69% = D, <60% = F scale will be used. Students' final grades will be determined as follows:

Students DOING research proposal: Students NOT DOING the research proposal :

• Project 35% • Project 40%

• Article Review 5% • Article Review 10%

• Quiz 10% • Quiz 10%

• Final Exam 15% • Final Exam 15%

• Lab Grade 25% • Lab Grade 25%

• Research Proposal 10%

It is the policy of the University to make reasonable accommodations for qualified individuals with disabilities. Students who may have special needs because of a physical or learning disability are encouraged to contact Disability Support Services ASAP (234 Student Union I) at 993-3247. Students with disabilities who are in need of accommodation relative to class attendance/arrival, course requirements, or related aspects of course performance and who have already processed the necessary paperwork with Disability Support Services must initiate such a request in writing immediately, and prior to any anticipated need, to the instructor. Such requests will be accommodated within the reasonable constraints of fairness and timeliness with regard to the instructor and the other students enrolled in the course.

(* = also available on the course website)

Plagiarism =

• Copying, word for word, greater than about 25% of a sentence from someone else's work and having the words appear to be your own words. [Note: This is regardless of 1) the type of other person's work (whether or not it was published) and 2) whether or not you have given the person a citation after the text or a reference in the bibliography].

• Using greater than 25% of the words in someone else's sentence by switching around the order of words or phrases and having the words appear to be your own words (same notes apply, as above).

• Paraphrasing someone else's ideas or findings or sentences without giving them a citation and reference.

• Using the same paper for this course which has been (or will be) turned in for another course.

Students are encouraged to collaborate and study together as much as possible throughout the course. For the project, students can assist each other in the form of defining and narrowing down the data set, discussing the assignment, proofreading drafts, and doing analyses together, but the student whose name appears on Phase 2-4 of the project must be the author, and the research questiions asked, analyses performed, and interpretation given need to be individual. For collaborative papers and article review, both students must contribute equally to the project, including relatively equal contributions to the actual writing. Violations of the Honor Code will not be tolerated in this course and will be immediately reported according to GMU procedures.

Lab grades will consist of the following:

• Homeworks 50%

• Oral Presentation 20%

• In-Class Lab Activities

/ Participation / Attendance 25%

• Item Submission 5%

Lab Activities/Participation and Lab Switching— In order to receive credit for the lab activity/participation on a given week, students must attend their own scheduled/registered lab. Switching labs without prior approval and arrangements made with both lab instructors, will result in the student not receiving credit for attending/ participating in that week’s lab. If you have an urgent need to switch labs, email your lab instructor and the lab instructor whose lab you would like to attend with your reason and await approval.

Collaboration — If desired, students may collaborate with a maximum of one other student (from the same lab section) on any and all in-class lab activities and lab homeworks. With this option, students turn in one copy of their work with both names. Partners are renegotiated for each week/assignment (i.e., working together once with one person doesn’t mean that you have to team up this way each time).

Late Policy — No late work will be accepted. All homework will be due on the dates clearly listed on the syllabus. All in-class lab activities will be due at the end of the lab session. Students with truly exceptional circumstances may request but are not guaranteed exceptions to this policy. (NOTE — The same policy holds for assignments in the lecture [article review, project phases…])

Redo Policy — Due to the nature of the assignments this semester, re-doing work for additional points will not be an option this semester. All grades will be based on what was originally turned in.

Word Processing — All work that is done outside of lab and turned in must be typed/word processed (except for the rare instance of hand calculations — even with these, however, the interpretation part of assignment must be typed). Five points will be deducted from work turned in that is not typed. Work done (and turned in the same day) in-class/lab may be hand written.

Supplies. Due to the fact that students will be working extensively with a large database in SPSS, it is strongly recommended that they obtain a ZIP disk on which to save work this semester. Also, bring your course notes and text books/readings to lab each week.

Name ___________________________________________

SS# ___________________________________________

Program/Year __________________________________________

Phone Number(s) ___________________________________________

___________________________________________

Primary Email Address ___________________________________________

GMU (Mason) Username ___________________________________________

(i.e., awinsler)

Previous (Pre PSYC 611) Statistics Coursework Taken:

Course Taken _______________________ Year ___________ Grad / Undergrad

Course Taken _______________________ Year ___________ Grad / Undergrad

Course Taken _______________________ Year ___________ Grad / Undergrad

Course Taken _______________________ Year ___________ Grad / Undergrad

(* = Required reading for this course)

Klahr, D., & Simon, H.A. (1999). Studies of scientific discovery: Complementary approaches and convergent findings. Psychological Bulletin, 125, 524-543.

McCall, M.W., & Bobko, P. (1990). Research methods in the service of discovery. In M.D. Dunnette & L.M. Hough (Eds.), Handbook of industrial and organizational psychology (2nd ed.) (Vol. 1) (pp. 381-418). Palo Alto, CA: Consulting Psychologists Press.

McGuire, W. J. (1997). Creative hypothesis generating in psychology: Some useful heuristics. Annual

Review of Psychology, 48, 1-30.

Phillips, D.C. (1987). Philosophy, science, and social policy: Contemporary methodological controversies in social science and related applied fields of research. Elmsford, NY: Pergammon.

Cooper, H., DeNeve, K., & Charlton, K. (1997). Finding the missing science: The fate of studies submitted for review by a human subjects committee. Psychological Methods, 2, 447-452.

Fine, M. A., & Kurdek, L. A. (1993). Reflections on determining authorship credit and authorship order on faculty-student collaborations. American Psychologist, 48, 1141-1147.

Rosnow, R. L. (1997). Hedgehogs, foxes, and the evolving social contract in psychological science: Ethical challenges and methodological opportunities. Psychological Methods, 2, 447-452.

Sieber, J. E. (1998). Planning ethical responsible research. In L. Bickman & D. J. Rog (Eds.), Handbook of applied social research methods (pp. 127-156). Thousand Oaks, CA: Sage.

Gully, S. (1993). Surviving the thesis/dissertation process. The Industrial-Organizational Psychologist, 31, 95-98.

Boruch, R. F. (1998). Randomized controlled experiments for evaluation and planning. In L. Bickman & D. J. Rog (Eds.), Handbook of applied social research methods (pp. 161-192). Thousand Oaks, CA: Sage.

*Keren, G. (1993). Between- or within-subjects design: A methodological dilemma. In G. Keren & C. Lewis (Eds.), A handbook for data analysis in the behavioral sciences: Methodological issues (pp. 257-272). Hillsdale, NJ: Erlbaum.

Reese, H. W. (1997). Counterbalancing and other uses of repeated-measures Latin-square designs: Analyses and interpretations. Journal of Experimental Child Psychology, 64, 137-158.

Heinsman, D. T., & Shadish, W. R. (1996). Assignment methods in experimentation: When do

nonrandomized experiments approximate answers from randomized experiments? Psychological Methods, 1, 154-169.

Lipsey, M.W., & Cordray, D.S. (2000). Evaluation methods for social intervention. Annual Review of Psychology, 51, 345-375.

*McCall, R., Green, B.L., Strauss, M.S., & Groark, C. (1998). Issues in community-based research and program evaluation. In W. Damon (Ed.) I.E.Sigel & A. Renninger (Vol. Eds.), Handbook of child psychology - 5th Edition - Volume 4: Child psychology in practice (pp. 955-997). New York: Wiley & Sons.

McClelland, G. H. (1997). Optimal design in psychological research. Psychological Methods, 2, 3-19.

Reichardt, C. S., & Mark, M. M. (1998). Quasi-experiments. In L. Bickman & D. J. Rog (Eds.),

Handbook of applied social research methods (pp. 193-228). Thousand Oaks, CA: Sage.

Edington, E.S. (1987). Randomized single-subject experiments and statistical tests. Journal of Counseling Psychology, 34, 437-442.

McGuigan, F.J. (1990). Experimental psychology: Methods of research (5th ed.). Englewood Cliffs, NJ: Prentice Hall. [Chapter 12 - "Experimental Design: Single Subject (N = 1) Research"].

Birnbaum, M. H. (Ed.). (2000). Psychological experiments on the Internet. San Diego: Academic Press.

Birnbaum, M. H. (2000). Introduction to behavioral research on the internet. Upper Saddle River, NJ: Prentice Hall.

Dawis, R. V. (1987). Scale construction. Journal of Counseling Psychology, 34, 481-489.

Dilman, D.A. (1991). The design and administration of mail surveys. Annual Review of Sociology, 17, 225-249.

Fowler, F. J. (1998). Design and evaluation of survey questions. In L. Bickman & D. J. Rog (Eds.),

Handbook of applied social research methods (pp. 343-374). Thousand Oaks, CA: Sage.

Hinkin, T.R., (1995). A review of scale development practices in the study of organizations. Journal of Management, 21, 967-988.

*Hinkin, T. R. (1998). A brief tutorial on the development of measures for use in survey questionnaires.

Organizational Research Methods, 1, 101-121.

Krosnick, J. A. (1999). Survey research. Annual Review of Psychology, 50, 537-567.

Lavrakas, P. J. (1998). Methods for sampling and interviewing in telephone surveys. In L. Bickman & D. J. Rog (Eds.), Handbook of applied social research methods (pp. 429-472). Thousand Oaks, CA: Sage.

Magione, T. W. (1998). Mail surveys. In L. Bickman & D. J. Rog (Eds.), Handbook of applied social

research methods (pp. 399-428). Thousand Oaks, CA: Sage.

Van Kammen, W. B., & Stouthamer-Louber, M. (1998). Practical aspects of interview data collection and data management. In L. Bickman & D. J. Rog (Eds.), Handbook of applied social research methods (pp. 375-398). Thousand Oaks, CA: Sage.

*Atkinson, P., & Hammersley, M. (1994). Ethnography and participant observation. In N.K. Denzin & Y. S. Lincoln (Eds.), Handbook of qualitative research (pp. 248-261). Thousand Oaks, CA: Sage.

Denzin, N.K., & Lincoln, Y.S. (Eds.). (2000). Handbook of qualitative research (2nd Ed.). Thousand Oaks, CA: Sage.

Eisenhardt, K. M. (1989). Building theories from case study research. Academy of Management Research, 14, 532-550.

McKeganey, N. (1995). Quantitative and qualitative research in the addictions: An unhelpful divide. Addiction, 90, 749-751.

Ogborne, A.C. (1995). Unhelpful divide but important distinction. Addiction, 90, 755-757.

Maxwell, J. A. (1998). Designing a qualitative study. In L. Bickman & D. J. Rog (Eds.), Handbook of applied social research methods (pp. 69-100). Thousand Oaks, CA: Sage.

*Stake, R.E. (2000). Case studies. In N.K. Denzin & Y. S. Lincoln (Eds.), Handbook of qualitative research (pp. 435-454). Thousand Oaks, CA: Sage.

Stewart, D. W., & Shamdasani, P. N. (1998). Focus group research: Exploration and discovery. In L.

Bickman & D. J. Rog (Eds.), Handbook of applied social research methods (pp. 505-526). Thousand Oaks, CA: Sage.

Sullivan, M.L. (1998). Integrating qualitative and quantitative methods in the study of developmental psychopathology in context. Development and Psychopathology, 10, 377-393.

Bakeman, R., & Gottman, J.M. (1997). Observing interaction: An introduction to sequential analysis (2^nd ed.). New York: Cambridge University Press.

Bakeman, R., & Quera, V. (1995). Analyzing interaction: Sequential analysis with SDIS and GSEQ. New York: Cambridge University Press.

Bedeian, A. G., Day, D. V., Edwards, J. R., Tisak, J., & Smith, C. S. (1994). Difference scores: Rationale, formulation and interpretation. Journal of Management, 20, 673-698.

Cliff, N. (1991). Ordinal methods in the assessment of change. In L.M. Collins & J.L. Horn (Eds.), Best methods for the analysis of change (pp. 34-46). Washington, DC: American Psychological Association.

*Francis, D.J., Fletcher, J.M., Stuebing, K.K., Davidson, K.C., & Thompson, N.M. (1991). Analysis of change: Modeling individual growth. Journal of Consulting and Clinical Psychology, 59, 27-37.

Kraemer, H. C. (1994). Special methodological problems of childhood developmental follow-up studies: Focus on planning. In S.L. Friedman & H.C. Haywood (Eds.), Developmental follow-up: Concepts, domains, and methods (pp. 259-276). San Diego, CA: Academic Press.

Kuhn, D. (1995). Microgenetic study of change: What has it told us? Psychological Science, 6, 133-139.

Miller, S. (1998). Developmental research methods (2nd ed.). Englewood Cliffs, NJ: Prentice Hall.

Patterson, G.R. (1995). Orderly change in a stable world: The antisocial trait as a chimera. In J.M. Gottman (Ed.), The analysis of change (pp. 83-101). Mahwah, NJ: Lawrence Erlbaum Associates.

Rogosa, D. (1995). Myths and methods: "Myths about longitudinal research" plus supplemental questions. In J.M. Gottman (Ed.), The analysis of change (pp. 3-66). Mahwah, NJ: Erlbaum.

Siegler, R.S., & Crowley, K. (1991). The microgenetic method: A direct means for studying cognitive development. American Psychologist, 46, 606-620.

Skinner, C. (1991). Time series. In P. Lovie & A.D. Lovie (Eds.), New developments in statistics for psychology and the social sciences (pp. 174-198). New York: Routledge.

Van der Kamp, L.J., & Bijleveld, C.C.J.H. (1998). Methodological issues in longitudinal research. In C.C.J.H. Bijleveld & L.J. Van der Kamp (Eds.), Longitudinal data analysis: Designs, models, & methods (pp. 1-45). Thousand Oaks, CA: Sage Publications.

*Cortina, J.M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology, 78, 98-104.

Schmidt, F.L., & Hunter, J.E. (1996). Measurement error in psychological research: Lessons from 26 research scenarios. Psychological Methods, 1, 199-223.

Traub, R. E. (1994). Reliability for the social sciences: Theory and applications. Newbury Park, CA: Sage Publications.

Austin, J. T., Boyle, K. A., & Lualhati, J. C. (1998). Statistical conclusion validity for organizational science researchers: A review. Organizational Research Methods, 1, 164-208.

Hollenbeck, J.R., Klein, H.J., O'Leary, A.M., & Wright, P.M. (1989). Investigation of the construct validity of a self-report measure of goal commitment. Journal of Applied Psychology, 74, 951-956.

Ilgen, D.R. (1986). Laboratory research: A question of when, not if. In E.A. Locke (Ed.), Generalizing from laboratory to field settings (pp. 257-267). Lexington, MA: Lexington Books.

Messick, S. (1995). Validity of psychological assessment: Validation of inferences from persons’

responses and performances as scientific inquiry into score meaning. American Psychologist, 50, 741-749.

*Mook, D.G. (1983). In defense of external invalidity. American Psychologist, 38, 379-387.

Sussmann, M., & Robertson, D.U. (1986). The validity of validity: An analysis of validation study designs. Journal of Applied Psychology, 71, 461-468.

Allison, D. B., Allison, R. L., Faith, M. S., Paultre, F., & Pi-Sunyer, F. X. (1997). Power and money:

Designing statistically powerful studies while minimizing financial costs. Psychological Methods, 2, 20-33.

Cohen, J. (1988). Statistical power analyis for the behavioral sciences (2^nd Ed.) Hillsdale, NJ: Erlbaum.

*Cohen, J. (1994). The Earth is round (p < .05). American Psychologist, 49, 997-1003.

*Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155-159.

Kraemer, H.C. (1987). How many subjects: Statistical power analysis in research. Newbury Park, CA: Sage.

Lipsey, M. W. (1998). Design sensitivity: Statistical power for applied experimental research. In L.

Bickman & D. J. Rog (Eds.), Handbook of applied social research methods (pp. 39-68). Thousand Oaks, CA: Sage.

Cortina, J.M., & Dunlap, W.P. (1997). On the logic and purpose of significance testing. Psychological Methods, 2, 161-172.

Cortina, J.M., & Folger, R.G. (1998). When is it acceptable to accept a null hypothesis: No way Jose? Organizational Research Methods, 1, 334-350.

*Cortina, J., & Nouri, H. (2000). Effect size for ANOVA designs. Newbury Park, CA: Sage Publications.

*McCartney, K., & Rosenthal, R. (2000). Effect size, practical importance, and social policy for children. Child Development, 71, 173-180.

*Nickerson, R.S. (2000). Null hypothesis significance testing: A review of an old and continuing controversy. Psychological Methods, 5, 241-301.

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Rosnow, R.L., Rosenthal, R., & Rubin, D.B. (2000). Contrasts and correlations in effect-sizes estimation. Psychological Science, 11, 446-453.

Schmidt, F.L. (1996). Statistical significance testing and cumulative knowledge in psychology: Implications for training of researchers. Psychological Methods, 1, 115-129.

*Behrens, J. T. (1997). Principles and procedures of exploratory data analysis. Psychological Methods, 2, 131-160.

Cohen, J. (1983). The cost of dichotomization. Applied Psychological Measurement, 7, 249-253.

Fitzgerald, L.F., & Hubert, L.J. (1987). Multidimensional scaling: Some possibilities for counseling psychology. Journal of Counseling Psychology, 34, 469-480.

Huff, D. (1954). How to lie with statistics. NY: Norton.

Lovie, S., & Lovie, P. (1991). Graphical methods for exploring data. In P. Lovie & A.D. Lovie (Eds.), New developments in statistics for psychology and the social sciences (pp. 19-48). New York: Routledge.

*Maxwell, S.E., & Delaney, H.D. (1993). Bivariate median splits and spurious statistical significance. Psychological Bulletin, 113, 181-190.

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*Smith, P.C., Budzeika, K.A., Edwards, N.A., Johnson, S.M., & Bearse, L.N. (1986). Guidelines for clean data: Detection of common mistakes. Journal of Applied Psychology, 71, 457-460.

*Tabachnick, B.G., & Fidell, L.S. (1996). Using multivariate statistics (3rd ed.). New York: Harper Collins. (Chapter 4- "Cleaning up your act: Screening data prior to analysis")

*Games, P.A. (1990). Alternative analyses of repeated-measure designs by ANOVA and MANOVA. In A. Von Eye (Ed.), Statistical methods in longitudinal research Vol. 1: Principles and structuring change (pp. 81-121). San Diego, CA: Academic Press.

Hertzog, C. (1994). Repeated measures analysis in developmental research: What our ANOVA text didn't tell us. In S.H. Cohen & H.W. Reese (Eds.), Life-span developmental psychology: Methodological contributions (pp. 187-222). Hillsdale, NJ: LEA.

Cliff, N. (1993). Dominance statistics: ordinal analyses to answer ordinal questions. Psychological Bulletin, 114, 494-509.

Gibbons, J.D. (1993). Nonparametric statistics: An introduction. Newbury Park, CA: Sage.

Hildebrand, D.K., Laing, J.D., & Rosenthal, H. (1977). Analysis of ordinal data. Newbury Park, CA: Sage.

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Von Eye, A. (1988). Some multivariate developments in nonparametric statistics. In J.R. Nesselroade & R.B. Catell (Eds.), Handbook of multivariate experimental psychology (2^nd Ed.) (pp. 367-398). New York: Plenum.

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Zimmerman, D.W., & Zumbo, B.D. (1993b). Relative power of the Wilcoxon test, the Friedman test, and repeated-measures ANOVA on ranks. Journal of Experimental Education, 62, 75-86.

*Von Eye, A., & Schuster, C. (2000). The odds of resilience. Child Development, 71, 563-566.

Von Eye, A., & Niedermeir, K.E. (1999). Statistical analysis of longitudinal categorical data in the social and behavioral sciences. Mahwah, NJ: Erlbaum.

Fabrigar, L.R., Wegener, D.T., MacCallum, R.C., & Straha, E.J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4, 272-299.

Ford, J. K., MacCallum, R. C., & Tait, M. (1986). The application of exploratory factor analysis in applied psychology: A critical review and analysis. Personnel Psychology, 39, 291-314.

*Tinsley, H.E.A., & Tinsley, D.J. (1987). Uses of factor analysis in counseling psychology research. Journal of Counseling Psychology, 34, 414-424.

Bray, J. H., & Maxwell, S. E. (1982). Analyzing and interpreting significant MANOVAs. Review of Educational Research, 52, 340-367.

Bray, J. H., & Maxwell, S. E. (1985). Multivariate analysis of variance. Newbury Park, CA: Sage.

*Haase, R. F., & Ellis, M. V. (1987). Multivariate analysis of variance. Journal of Counseling Psychology, 34, 404-413.

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

*Baron, R.M., & Kenny, D.A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173-1182.

Berry, W.D. (1993). Understanding regression assumptions. Newbury Park, CA: Sage.

Berry, W.D., & Feldman, S. (1985). Multiple regression in practice. Newbury Park, CA: Sage.

Chaterjee, S., & Price, B. (1991). Regression analysis by example (2^nd Ed.). New York: Wiley.

Cortina, J. (1993). Interaction, nonlinearity, and multicollinearity: Implications for multiple regression. Journal of Management, 19, 915-922.

Dunlap, W. P., & Kemery, E. R. (1988). Effects of predictor intercorrelations and reliabilities on moderated multiple regression. Organizational Behavior and Human Decision Processes, 41, 248-258.

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* Stevens, J. P. (1984). Outliers and influential data points in regression analysis. Psychological Bulletin, 95, 334-344.

*Wampold, B.E., & Freund R.D. (1987). Use of multiple regression in counseling psychology; A flexible research strategy. Journal of Counseling Psychology, 34, 372-382.

Betz, N. E. (1987). Use of discriminant analysis in counseling psychology research. Journal of Counseling Psychology, 34, 393-403.

Bergman, L.R., & Magnusson, D. (1997). A person-oriented approach in research on developmental psychopathology. Development and Psychopathology, 9, 291-319.

Borgen, F.H., & Barnett, D.C. (1987). Applying cluster analysis in counseling psychology research. Journal of Counseling Psychology, 34, 456-468.

Cooper, H. M., & Lindsay, J. L. (1998). Research synthesis and meta-analysis. In L. Bickman & D. J. Rog (Eds.), Handbook of applied social research methods (pp. 315-339). Thousand Oaks, CA: Sage.

Glass, G.V. (1976). Primary, secondary, and meta-analysis of research. Educational Researcher, 5, 3-8.

Hedges,L.V. (1987), How hard is hard science, How soft is soft science. American Psychologist, 42, 443-455.

Hedges, L. V., & Olkin, I. (1985). Statistical methods for meta-analysis. San Diego, CA: Academic Press.

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Orwin, R.G. & Cordray, D.S. (1985). Effects of deficient reporting on meta-analysis" A conceptual framework and reanalysis. Psychological Bulletin, 97, 134-147.

Schmidt, F.L. (1992), What do data really mean? Research findings, meta-analysis, and cumulative knowledge in psychology. American Psychologist, 47, 1173-1181.

Slavin, R. E. (1984). Meta-analysis in education: How has it been used? Educational Researcher, 13, 6-15.

Carlberg, C. G., Kulik, C. C., Kulik, J. A., Johnson, D. W., Johnson, R. Maruyama, G., Kavale, K., Lysakowski, R. S., Pflaum, S. W., & Walberg, H. J. (1984). Meta-analysis in education: A reply to Slavin. Educational Researcher, 13, 16-23.

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