Statistics Papers for Download
This is a list of papers we have found useful. Many of the links are
restricted to certain IP addresses and may
only be available if you are connecting from a UCLA IP address.
As of Fall 2005 we are no longer actively seeking out and maintaining this
list because of the release of
http://scholar.google.com. You can use Google Scholar to perform fairly
comprehensive searches of research papers based on the search criteria you
specify. You can try this for yourself by visiting
http://scholar.google.com or by using
the search box below.
Assumptions

A note on ANOVA assumptions and robust analysis for a
crossover study by Xun Chen, PengLiang Zhao and Ji Zhang from Statistics in Medicine, 2002, Volume 21, pages 1377–1386

The importance of the normality assumption in large
public health data sets by Ziding Feng Paula Diehr Arthur Peterson and
Dale McLerran from Annual Reviews of Public
Health, 2001, Volume 22, pages 167187. Thomas Lumley, Paula Diehr, Scott
Emerson, and Lu Chen from Annual Reviews of Public
Health, 2002, Volume 23, pages
151169.
Bootstrap methods
Item Response Theory

An
Introduction to Modern Measurement Theory by Bryce B. Reeve of the
National Cancer Institute

Item Response Theory and Health Outcomes Measurement in the 21st Century.
Hays, Ron; Morales, Leo; Reise, Steve P.

Equating Health Status Measures With Item Response Theory: Illustrations
With Functional Status Items. McHorney, Colleen A; Cohen, Allan S. PhD

Response to Hays et al and McHorney and Cohen: Emergence of Item Response
Modeling in Instrument Development and Data Analysis. Hambleton, Ronald K.

Response to Hays et al and McHorney and Cohen: A Discussion of Item Response
Theory and Its Applications in Health Status Assessment. Cella, David PhD;
Chang, ChihHung

Response to Hays et al and McHorney and Cohen: Practical Implications of
Item Response Theory and Computerized Adaptive Testing: A Brief Summary of
Ongoing Studies of Widely Used Headache Impact Scales. Ware, John E. Jr;
Bjorner, Jakob B,. Kosinski, Mark MA

Item response theory: applications of modern test theory in medical
education by Steven Downing from Medical Education

Psychometrics: From practice to theory and back by William Stout from
Psychometrika, December 2002
Factor Invariance
 Thompson, M. S., & Green, S. B.
(2006). Evaluating betweengroup differences in latent variable means. In G. R.
Hancock & R. O. Mueller (Eds.),
A Second
Course in Structural Equation Modeling (pp. 119169).
Greenwich, CT: Information Age Publishing, Inc.
 Wicherts, J.M., Dolan, C.V., & Hessen, D.J.(2005). Stereotype threat and
group differences in test performance: A question of measurement invariance.
Journal of Personality and Social Psychology, 89, 696716.
STinvardef.pdf
LISREL FILES:
Zipped
 Millsap, R.E. and J. YunTein,
Assessing factorial invariance in orderedcategorical measures. Multivariate
Behavioral Research, 2004. 39(3): p. 479516.
 Wicherts, J.M., Dolan, C.V., Hessen, D.J., Oosterveld, P., Baal, G.C.M.
van, Boomsma, D.I., & Span, M.M. (2004). Are intelligence tests measurement
invariant over time? Investigating the nature of the Flynn effect.
Intelligence, 32, 509537.
flynninvarrev.pdf Lisrel files:
zipped
 Dolan, C.V. Roorda, W., and Wicherts, J. M. (2004). Two failures of Spearman's hypothesis: The GATB
in Holland and the JAT in South Africa. Intelligence, 32,
155173 (PDF
about 407 Kb).
 Taub, G. E., McGrew, K. S., & Witta, E. L. (2004). A confirmatory
analysis of the factor structure and crossage invariance of the Wechsler
Adult Intelligence Scale  Third Edition. Psychological Assessment, 16,
8589.
(cannot find pdf on web)
 *Meade, A. W., & Lautenschlager, G. J. (2004).
A comparison of item response
theory and confirmatory factor analytic methodologies for establishing
measurement equivalence/invariance. Organizational Research Methods, 7, 361388.
 Levine, D. W., Kaplan, R. M., Kripke, D. F., Bowen, D. J., Naughton, M. J., &
Shumaker, S. A. (2003). Factor structure and measurement invariance of the
women's health initiative insomnia rating scale. Psychological Assessment, 15,
123136. (cannot find pdf on web)
 Antonakis, J., Avolio, B. J., & Sivasubramaniam, N. (2003).
Context and
leadership: An examination of the ninefactor FullRange Leadership Theory using
the Multifactor Leadership Questionnaire (MLQ Form 5X). Leadership
Quarterly, 14(3), 261295.
 Breithaupt, K., & Zumbo, B. D. (2002). Sample invariance of the structural
equation model and the item response model: A case study. Structural Equation
Modeling, 9, 390412. (cannot find pdf on web)
 * Vandenberg, R. J., & Lance, C. E. (2000).
A review and synthesis of the measurement invariance literature:
Suggestions, practices, and recommendations for organizational research.
Organizational Research Methods, 3 (1), 469.
 *Cheung, G., & Rensvold, R. (1999).
Testing factorial
invariance across groups: A reconceptualization and proposed new method.
Journal of Management, 25(1), 127.
 * Steenkamp, J.B. E. M., & Baumgartner, H. (1998).
Assessing measurement invariance in crossnational consumer research. Journal
of Consumer Research, 25, 7890. (cannot find pdf on web)
 Reise, S. P., Widaman, K. F., & Pugh, R. H. (1993). Confirmatory factor analysis and item response theory: Two approaches for
exploring measurement invariance. Psychological Bulletin, 114, 552566.
 Meredith, W. (1993). Measurement invariance, factor analysis and factorial
invariance. Psychometrika, 58, 525543.
 Horn, J. L., & McArdle, J. J. (1992). A practical and theoretical guide to
measurement invariance for aging research. Experimental Aging Research, 18,
117144. (cannot find pdf on web)
 * Byrne, B., Shavelson, R. J., & Muthén, B. (1989).
Testing for the equivalence of factor covariance and mean structures: The
issue of partial measurement invariance. Psychological Bulletin, 105
(3), 456466.
 Also see
Byrne, B. M. (2001). Structural equation modeling with AMOS: Basic concepts,
applications, and programming. Mahwah, NJ: Lawrence Erlbaum.
Latent Growth Analysis

A latent variable
framework for power estimation and analyses within intervention contexts.
Journal of Psychopathology and Behavioral Assessment, Vol 24, pp. 112, by
Duncan, T.E., Duncan, S.C., Strycker, L.A., & Li, F. (2002).

Growth mixture modeling of adolescent alcohol use data: Chapter addendum
to An Introduction to Latent Variable Growth Curve Modeling: Concepts, Issues,
and Applications. Eugene, OR: Oregon Research Institute. by Duncan, T. E.,
Susan, S. C., Strycker, L. A., & Okut, H. (2002).

Latent Growth Curve Analysis: A Gentle Introduction by Alan C. Acock
and Fuzhong Li

Latent Curve Analysis: A Manual for Research Data Analysts by Fuzhong Li
and Alan C. Acock
Logistic Regression
Missing Data

Imputation of Missing Item Responses: Some Simple Techniques by Mark
Huisman from Quality and Quantity, 2000, #34, 331351.

Multiple
Imputation in Practice: Comparison of Software Packages for Regression Models
with Missing Variables by Nicholas Horton from The American Statistician,
2001, Volume 55, Pages 244254.

Using auxiliary data for parameter estimation with nonignorably missing
outcomes by Ibrahim JG, Lipsitz SR and
Horton NJ. from Journal of the Royal Statistical
Society: Series C (Applied Statistics), 2001, Volume
50, #3, pages 361373.

Comparison of Two
Multiple Imputation Procedures in a Cancer Screening Survey by Coen A.
Bernaards, Melissa M. Farmer, Karen Qi, Gareth S. Dulai, Patricia A. Ganz,
Katherine L. Kahn from
UCLA Preprint Server.
 Handling Missing Data Case Study from the Statistical Society of Canada
Multilevel Models
Research Design & Causal Inference

Reference Guide on Statistics by David H. Kaye & David A. Freedman from
the Federal Judicial Center

How Science Works by David Goodstein from the Federal Judicial Center

Confounding in Health Research by Sander Greenland and Hal Morgenstern
from Annual Reviews of Public Health, 2001,
Volume 22, pages 189212.

The Design
and Analysis of Social Interaction Research by David A. Kenny
from Annual Reviews
of Psychology, 1996,
Volume 47, pages
5986.

Evaluation
Methods for Social Intervention by Mark W. Lipsey and David S. Cordray,
from Annual Reviews of Psychology, 2000, Volume 51, pages 345375.

Methodological Issues in Psychopathology Research
by K. J. Sher and T. J. Trull from
Annual Reviews of Psychology, 1996, Volume
47, pages 371400.

Selected Statistical Issues in Group Randomized Trials by Ziding Feng Paula Diehr Arthur Peterson and
Dale McLerran from Annual Reviews of Public Health, 2001,
Volume 22, pages 167187.

Comparing
Personal Trajectories and Drawing Causal Inferences from Longitudinal Data
by Stephen W. Raudenbush from
Annual Reviews of Psychology, 2001, Volume
52, pages 501525.

The Estimation
of Causal Effects from Observational Data by Christopher Winship
and Stephen L. Morgan from Annual
Reviews of Sociology,
1999, Volume 25, pages 659706.

Does X really cause Y?
by Bryan Dowd and Robert Town from Academy Health
Regression
Survey Research
Survival Analysis
Other

British Medical Journal
Statistics Notes

Categorical Data Analysis in Public Health by
John S. Preisser and Gary G.
Koch from Annual Reviews of Public
Health, 1997, Volume 18, pages 5182.

Categorical
Data Analysis by Thomas D. Wickens from
Annuual Reviews of Psychology,
1998, Volule 49, pages
537558.
 Covariance Structure Analysis: Statistical Practice, Theory,
and Directions by Peter M. Bentler and Paul Dudgeon from
Annual Reviews of Psychology, 1996, Volume 47, pages 563592.

Statistical
Graphics: Mapping the Pathways of Science by
Howard Wainer and Paul F. Velleman from Annual
Reviews of Psychology.
2001 , Volume 52, pages 305335.
 Latent
Variables in Psychology and the Social Sciences
by Kenneth A. Bollen from Annual Reviews of
Psychology, 2002, Volume 53,
pages 605634.

Meta Analysis: Recent Developments in Quantitative
Methods for Literature Reviews by R. Rosenthal
and M. R. DiMatteo from Annual Reviews of Psychology,
2001, Volume 52, pages
5982.
 Review of
Software to fit Generalized Estimating Equation (GEE) Regression Models.
by Horton NJ and Lipsitz SR. from The
American Statistician,
1999, Volume 53,
pages 160169.

The sample size for a clinical trial: A Bayesiandecision theoretic approach
by Jerry Halpern, Byron Wm. Brown Jr, and John Hornberger from Statistics in
Medicine, 2001, 825840.
 Some practical
guidelines for effective samplesize determination by Russell V. Lenth
from University of Iowa

Achieving graphical excellence: Suggestions and methods for creating
highquality visual displays of experimental data by David L. Schriger,
MD, MPH and Richelle J. Cooper, MD, MSHS from Annals of Emergency Medicine,
January 2001, Volume 37 Number 1.

Statistical
Analysis of Repeated Measures Data Using SAS Procedures by Littell RC,
Henry PR, and Ammerman CB (1998), Journal of Animal Science, 76, 12161231.
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