Statistical Analysis of Correlated Ordinal Data: Application to Cluster Randomization Trials

.............................................................................................................................. ii Acknowledgments.............................................................................................................. iii Table of

[1]  F. E. Satterthwaite.  Synthesis of variance , 1941 .

[2]  F. Yates.  The analysis of contingency tables with groupings based on quantitative characters. , 1948, Biometrika.

[3]  W. G. Cochran.  Some Methods for Strengthening the Common χ 2 Tests , 1954 .

[4]  W. A. Scott,et al.  Reliability of Content Analysis ; The Case of Nominal Scale Cording , 1955 .

[5]  P. Armitage.  Tests for Linear Trends in Proportions and Frequencies , 1955 .

[6]  D. Cox.  The Regression Analysis of Binary Sequences , 1958 .

[7]  J. Aitchison,et al.  Maximum-Likelihood Estimation of Parameters Subject to Restraints , 1958 .

[8]  W. Haenszel,et al.  Statistical aspects of the analysis of data from retrospective studies of disease. , 1959, Journal of the National Cancer Institute.

[9]  Jacob Cohen.  A Coefficient of Agreement for Nominal Scales , 1960 .

[10]  A. Stroud,et al.  Gaussian quadrature formulas , 1966 .

[11]  Jacob Cohen,et al.  Weighted kappa: Nominal scale agreement provision for scaled disagreement or partial credit. , 1968 .

[12]  G. Koch,et al.  Analysis of categorical data by linear models. , 1969, Biometrics.

[13]  P. McCullagh,et al.  Generalized Linear Models , 1972, Predictive Analytics.

[14]  Jacob Cohen,et al.  The Equivalence of Weighted Kappa and the Intraclass Correlation Coefficient as Measures of Reliability , 1973 .

[15]  B. Everitt,et al.  Statistical methods for rates and proportions , 1973 .

[16]  R. McKelvey,et al.  A statistical model for the analysis of ordinal level dependent variables , 1975 .

[17]  G G Koch,et al.  A general methodology for the analysis of experiments with repeated measurement of categorical data. , 1977, Biometrics.

[18]  D. Hinkley.  Jackknifing in Unbalanced Situations , 1977 .

[19]  R. Elston,et al.  Query: estimating "heritability" of a dichotomous trait. , 1977, Biometrics.

[20]  W. Hauck,et al.  Wald's Test as Applied to Hypotheses in Logit Analysis , 1977 .

[21]  J. Fleiss,et al.  The Reliability of Dichotomous Judgments: Unequal Numbers of Judges per Subject , 1979 .

[22]  P. McCullagh.  Regression Models for Ordinal Data , 1980 .

[23]  S. Brier.  Analysis of contingency tables under cluster sampling , 1980 .

[24]  G. Koch,et al.  Categorical Data Analysis: Some Reflections on the Log Linear Model and Logistic Regression. Part I: Historical and Methodological Overview* , 1981 .

[25]  A. Scott,et al.  The Effect of Two-Stage Sampling on Ordinary Least Squares Methods , 1982 .

[26]  J. Darroch,et al.  Categorical Data Analysis: Some Reflections on the Log Linear Model and Logistic Regression. Part II: Data Analysis , 1982 .

[27]  Bernard R. Rosner,et al.  Fundamentals of Biostatistics. , 1992 .

[28]  A. Agresti.  Analysis of Ordinal Categorical Data , 1985 .

[29]  H. White,et al.  Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties☆ , 1985 .

[30]  C. Cox,et al.  Pseudo maximum likelihood estimation for the dirichlet-multinomial distribution , 1985 .

[31]  L. A. Goodman.  The Analysis of Cross-Classified Data Having Ordered and/or Unordered Categories: Association Models, Correlation Models, and Asymmetry Models for Contingency Tables With or Without Missing Entries , 1985 .

[32]  M. Haber.  Maximum likelihood methods for linear and log-linear models in categorical data , 1985 .

[33]  A. Agresti,et al.  Analysis of Ordinal Categorical Data. , 1985 .

[34]  Morton B. Brown,et al.  Maximum likelihood methods for log-linear models when expected frequencies are subject to linear constraints , 1986 .

[35]  M. D. Hogan,et al.  The impact of litter effects on dose-response modeling in teratology. , 1986, Biometrics.

[36]  S. Zeger,et al.  Longitudinal data analysis using generalized linear models , 1986 .

[37]  A. Donner.  A Review of Inference Procedures for the Intraclass Correlation Coefficient in the One-Way Random Effects Model , 1986 .

[38]  F. Harrell,et al.  Partial Proportional Odds Models for Ordinal Response Variables , 1990 .

[39]  R. Tamura,et al.  The incorporation of historical control information in tests of proportions: simulation study of Tarone's procedure. , 1986, Biometrics.

[40]  W. Willett,et al.  Misinterpretation and misuse of the kappa statistic. , 1987, American journal of epidemiology.

[41]  Martin Bland,et al.  An Introduction to Medical Statistics , 1987 .

[42]  A. Donner,et al.  Analysis of data arising from a stratified design with the cluster as unit of randomization. , 1987, Statistics in medicine.

[43]  Allan Donner,et al.  A Procedure for Generating Group Sizes from a One-way Classification with a Specified Degree of Imbalance , 1987 .

[44]  R. Tamura,et al.  A stabilized moment estimator for the beta-binomial distribution. , 1987, Biometrics.

[45]  E. Korn,et al.  Choice of column scores for testing independence in ordered 2 X K contingency tables. , 1987, Biometrics.

[46]  B. Flay,et al.  The television school and family smoking prevention and cessation project. 1. Theoretical basis and program development. , 1988, Preventive medicine.

[47]  T. Mak.  Analysing Intraclass Correlation for Dichotomous Variables , 1988 .

[48]  A. Donner,et al.  The statistical analysis of multiple binary measurements. , 1988, Journal of clinical epidemiology.

[49]  J. Rao,et al.  The Analysis of Cross-Classified Categorical Data from Complex Sample Surveys , 1988 .

[50]  P. Albert,et al.  Models for longitudinal data: a generalized estimating equation approach. , 1988, Biometrics.

[51]  N. Jewell,et al.  Hypothesis testing of regression parameters in semiparametric generalized linear models for cluster correlated data , 1990 .

[52]  David W. Hosmer,et al.  Applied Logistic Regression , 1991 .

[53]  A. Donner,et al.  Adjustment of Frequently Used Chi-square Procedures for the Effect of Site-to-Site Dependencies in the Analysis of Dental Data , 1989, Journal of dental research.

[54]  R. Brant.  Assessing proportionality in the proportional odds model for ordinal logistic regression. , 1990, Biometrics.

[55]  A. Feinstein,et al.  High agreement but low kappa: I. The problems of two paradoxes. , 1990, Journal of clinical epidemiology.

[56]  M. Karim.  Generalized Linear Models With Random Effects , 1991 .

[57]  A. Agresti,et al.  Categorical Data Analysis , 1991, International Encyclopedia of Statistical Science.

[58]  A. Narayanan.  Maximum Likelihood Estimation of the Parameters of the Dirichlet Distribution , 1991 .

[59]  E H Wagner,et al.  Data analysis and sample size issues in evaluations of community-based health promotion and disease prevention programs: a mixed-model analysis of variance approach. , 1991, Journal of clinical epidemiology.

[60]  J. Kalbfleisch,et al.  A Comparison of Cluster-Specific and Population-Averaged Approaches for Analyzing Correlated Binary Data , 1991 .

[61]  A. Kristal,et al.  Selected methodological issues in evaluating community-based health promotion and disease prevention programs. , 1992, Annual review of public health.

[62]  A. Scott,et al.  A simple method for the analysis of clustered binary data. , 1992, Biometrics.

[63]  C. Perry,et al.  Results from a statewide approach to adolescent tobacco use prevention. , 1992, Preventive medicine.

[64]  D. Boos.  On Generalized Score Tests , 1992 .

[65]  C. Morrison,et al.  AIDS education for drug abusers: evaluation of short-term effectiveness. , 1992, American journal of public health.

[66]  S. Lipsitz.  Categorical data analysis. Alan Agresti, Wiley, New York, 1990. no. of pages: xv + 558. Price: £48.50, $72.95. ISBN: 0‐471‐85301‐1 , 1992 .

[67]  M. Piedmonte,et al.  On some small sample properties of generalized estimating equationEstimates for multivariate dichotomous outcomes , 1992 .

[68]  T. Yanagimoto,et al.  Moment estimators for the beta-binomial distribution , 1992 .

[69]  M. Gail,et al.  Aspects of statistical design for the Community Intervention Trial for Smoking Cessation (COMMIT). , 1992, Controlled clinical trials.

[70]  J. G. Morel,et al.  A finite mixture distribution for modelling multinomial extra variation , 1993 .

[71]  M. Segal,et al.  Design effects for binary regression models fitted to dependent data. , 1993, Statistics in medicine.

[72]  N. Breslow,et al.  Approximate inference in generalized linear mixed models , 1993 .

[73]  J. R. Landis,et al.  The analysis of longitudinal polytomous data: generalized estimating equations and connections with weighted least squares. , 1993, Biometrics.

[74]  D. Firth.  Bias reduction of maximum likelihood estimates , 1993 .

[75]  N. Laird,et al.  A likelihood-based method for analysing longitudinal binary responses , 1993 .

[76]  A. Scott,et al.  Tests for trend in developmental toxicity experiments with correlated binary data. , 1994, Risk analysis : an official publication of the Society for Risk Analysis.

[77]  D. Hedeker,et al.  A random-effects ordinal regression model for multilevel analysis. , 1994, Biometrics.

[78]  S. Lipsitz,et al.  Performance of generalized estimating equations in practical situations. , 1994, Biometrics.

[79]  S. Lipsitz,et al.  Analysis of repeated categorical data using generalized estimating equations. , 1994, Statistics in medicine.

[80]  M. Piedmonte,et al.  Small sample validity of latent variable models for correlated binary data , 1994 .

[81]  M. Eliasziw,et al.  A comparison of methods for testing homogeneity of proportions in teratologic studies. , 1994, Statistics in medicine.

[82]  D. Jacobs,et al.  PARAMETERS TO AID IN THE DESIGN AND ANALYSIS OF COMMUNITY TRIALS: INTRACLASS CORRELATIONS FROM THE MINNESOTA HEART HEALTH PROGRAM , 1994, Epidemiology.

[83]  G. Molenberghs,et al.  Marginal Modeling of Correlated Ordinal Data Using a Multivariate Plackett Distribution , 1994 .

[84]  Qing Liu,et al.  A note on Gauss—Hermite quadrature , 1994 .

[85]  D. Hedeker,et al.  Random-effects regression models for clustered data with an example from smoking prevention research. , 1994, Journal of consulting and clinical psychology.

[86]  A. Agresti,et al.  Simultaneously Modeling Joint and Marginal Distributions of Multivariate Categorical Responses , 1994 .

[87]  Y. Qu,et al.  Latent variable models for clustered ordinal data. , 1995, Biometrics.

[88]  J. Simpson,et al.  Accounting for cluster randomization: a review of primary prevention trials, 1990 through 1993. , 1995, American journal of public health.

[89]  D L DeMets,et al.  A comparison of methods for correlated ordinal measures with ophthalmic applications. , 1995, Statistics in medicine.

[90]  D J Schnell,et al.  A regression method for analysing ordinal data from intervention trials. , 1995, Statistics in medicine.

[91]  S. Kelder,et al.  Statistical design of the Child and Adolescent Trial for Cardiovascular Health (CATCH): implications of cluster randomization. , 1995, Controlled clinical trials.

[92]  P. McCullagh,et al.  Multivariate Logistic Models , 1995 .

[93]  D. Hedeker,et al.  The television, school, and family smoking prevention and cessation project. VIII. Student outcomes and mediating variables. , 1995, Preventive medicine.

[94]  P. Diggle.  Analysis of Longitudinal Data , 1995 .

[95]  D. Hedeker,et al.  MIXOR: a computer program for mixed-effects ordinal regression analysis. , 1996, Computer methods and programs in biomedicine.

[96]  Z. Feng,et al.  A comparison of statistical methods for clustered data analysis with Gaussian error. , 1996, Statistics in medicine.

[97]  B. Qaqish,et al.  Deletion diagnostics for generalised estimating equations , 1996 .

[98]  A Donner,et al.  Statistical considerations in the design and analysis of community intervention trials. , 1996, Journal of clinical epidemiology.

[99]  J. R. Landis,et al.  Population-averaged and cluster-specific models for clustered ordinal response data. , 1996, Statistics in medicine.

[100]  H. Brenner,et al.  Dependence of Weighted Kappa Coefficients on the Number of Categories , 1996, Epidemiology.

[101]  T. Lumley.  Generalized estimating equations for ordinal data: a note on working correlation structures. , 1996, Biometrics.

[102]  M. Lindstrom,et al.  A survey of methods for analyzing clustered binary response data , 1996 .

[103]  G. Tutz,et al.  Random effects in ordinal regression models , 1996 .

[104]  G. Glonek.  A class of regression models for multivariate categorical responses , 1996 .

[105]  S. Kelder,et al.  Outcomes of a field trial to improve children's dietary patterns and physical activity. The Child and Adolescent Trial for Cardiovascular Health. CATCH collaborative group. , 1996, JAMA.

[106]  S. Fortmann,et al.  The Stanford Nutrition Action Program: a dietary fat intervention for low-literacy adults. , 1997, American journal of public health.

[107]  M. Sherman,et al.  A comparison between bootstrap methods and generalized estimating equations for correlated outcomes in generalized linear models , 1997 .

[108]  D. Hedeker,et al.  Random effects probit and logistic regression models for three-level data. , 1997, Biometrics.

[109]  권오준,et al.  기관 문합 수기의 비교 실험 , 1997 .

[110]  P. Hannan,et al.  AIDS education in Tanzania: promoting risk reduction among primary school children. , 1997, American journal of public health.

[111]  C. McCulloch.  Maximum Likelihood Algorithms for Generalized Linear Mixed Models , 1997 .

[112]  S. Thompson.  The merits of matching in community intervention trials: a cautionary tale. , 1998, Statistics in medicine.

[113]  D. Kleinbaum,et al.  Anova for repeated ordinal data with small sample size? a comparison of anova, manova, wls and gee methods by simulation , 1998 .

[114]  David M. Murray,et al.  Design and Analysis of Group- Randomized Trials , 1998 .

[115]  D. Hedeker,et al.  A Multilevel Thresholds of Change Model for Analysis of Stages of Change Data , 1998 .

[116]  V. Abraira,et al.  Generalization of the Kappa coeficient for ordinal categorical data, multiple observers and incomplete designs , 1999 .

[117]  D. Firth,et al.  Estimating Intraclass Correlation for Binary Data , 1999, Biometrics.

[118]  M. Aitkin.  A General Maximum Likelihood Analysis of Variance Components in Generalized Linear Models , 1999, Biometrics.

[119]  J. Booth,et al.  Maximizing generalized linear mixed model likelihoods with an automated Monte Carlo EM algorithm , 1999 .

[120]  B. Rosner,et al.  Use of the Mann-Whitney U-test for clustered data. , 1999, Statistics in medicine.

[121]  W. Cumberland,et al.  Interval estimation for the intraclass correlation in dirichlet-multinomial data , 1999 .

[122]  M. Banerjee,et al.  Beyond kappa: A review of interrater agreement measures , 1999 .

[123]  A. Fielding.  Why use arbitrary points scores?: ordered categories in models of educational progress , 1999 .

[124]  H. Barnhart,et al.  Testing proportionality in the proportional odds model fitted with GEE. , 1999, Statistics in medicine.

[125]  G. Molenberghs,et al.  Pseudolikelihood Modeling of Multivariate Outcomes in Developmental Toxicology , 1999 .

[126]  E. Brunner,et al.  Nonparametric Analysis of Ordered Categorical Data in Designs with Longitudinal Observations and Small Sample Sizes , 2000 .

[127]  L. Ryan,et al.  Analysis of dichotomous outcome data for community intervention studies , 2000, Statistical methods in medical research.

[128]  D. Berridge,et al.  A continuation ratio random effects model for repeated ordinal responses. , 2000, Statistics in Medicine.

[129]  A. Agresti,et al.  Random Effects Modeling of Multiple Binomial Responses Using the Multivariate Binomial Logit‐Normal Distribution , 2000, Biometrics.

[130]  Allan Donner,et al.  Design and Analysis of Cluster Randomization Trials in Health Research , 2001 .

[131]  A. Sashegyi,et al.  Application of a generalized random effects regression model for cluster-correlated longitudinal data to a school-based smoking prevention trial. , 2000, American journal of epidemiology.

[132]  Scott L. Zeger,et al.  Marginalized Multilevel Models and Likelihood Inference , 2000 .

[133]  M. Fay,et al.  Small‐Sample Adjustments for Wald‐Type Tests Using Sandwich Estimators , 2001, Biometrics.

[134]  A. Agresti,et al.  Multinomial logit random effects models , 2001 .

[135]  T. Derouen,et al.  A Covariance Estimator for GEE with Improved Small‐Sample Properties , 2001, Biometrics.

[136]  C. Perucci,et al.  Application of random effect ordinal regression model for outcome evaluation of two randomized controlled trials , 2001, Statistics in medicine.

[137]  M. Mugford,et al.  WHO antenatal care randomised trial for the evaluation of a new model of routine antenatal care , 2001, The Lancet.

[138]  S G Thompson,et al.  Analysis of cluster randomized trials with repeated cross-sectional binary measurements. , 2001, Statistics in medicine.

[139]  W. Pan.  On the robust variance estimator in generalised estimating equations , 2001 .

[140]  Seung-Ho Kang,et al.  Tests for 2×K contingency tables with clustered ordered categorical data , 2001, Statistics in medicine.

[141]  A. Agresti,et al.  Modeling Clustered Ordered Categorical Data: A Survey , 2001 .

[142]  N. Goldman,et al.  Improved estimation procedures for multilevel models with binary response: a case‐study , 2001 .

[143]  R. Carroll,et al.  A Note on the Efficiency of Sandwich Covariance Matrix Estimation , 2001 .

[144]  S. Rabe-Hesketh,et al.  Reliable Estimation of Generalized Linear Mixed Models using Adaptive Quadrature , 2002 .

[145]  W. Pan,et al.  Small‐sample adjustments in using the sandwich variance estimator in generalized estimating equations , 2002, Statistics in medicine.

[146]  K. Lui.  Notes on Estimation of the General Odds Ratio and the General Risk Difference for Paired‐Sample Data , 2002 .

[147]  A. Agresti,et al.  The analysis of contingency tables under inequality constraints , 2002 .

[148]  H. Goldstein,et al.  Multilevel ordinal models for examination grades , 2003 .

[149]  R. D'Agostino,et al.  Robustness and power of analysis of covariance applied to ordinal scaled data as arising in randomized controlled trials , 2003, Statistics in Medicine.

[150]  D. Zucker.  Design and Analysis of Cluster Randomization Trials , 2003 .

[151]  B. Turnbull,et al.  Likelihood Inference for Exchangeable Binary Data with Varying Cluster Sizes , 2003, Biometrics.

[152]  N. C. Schaeffer,et al.  The Science of Asking Questions , 2003 .

[153]  P. Fink,et al.  Diagnosis of somatisation: effect of an educational intervention in a cluster randomised controlled trial. , 2003, The British journal of general practice : the journal of the Royal College of General Practitioners.

[154]  D. Hedeker.  A mixed‐effects multinomial logistic regression model , 2003, Statistics in medicine.

[155]  R. Glynn,et al.  Incorporation of Clustering Effects for the Wilcoxon Rank Sum Test: A Large‐Sample Approach , 2003, Biometrics.

[156]  J. Hagenaars,et al.  15 Ordinal longitudinal data analysis , 2003 .

[157]  A. Donner,et al.  Pitfalls of and controversies in cluster randomization trials. , 2004, American journal of public health.

[158]  J. Ware,et al.  Applied Longitudinal Analysis , 2004 .

[159]  D. Kendrick,et al.  Providing child safety equipment to prevent injuries: randomised controlled trial , 2004, BMJ : British Medical Journal.

[160]  A. Biswas.  Generating correlated ordinal categorical random samples , 2004 .

[161]  Jessica B. Janega,et al.  Design and analysis of group-randomized trials: a review of recent practices. , 2004, American journal of public health.

[162]  Jonathan L. Blitstein,et al.  Design and analysis of group-randomized trials: a review of recent methodological developments. , 2004, American journal of public health.

[163]  C. McCulloch,et al.  Small Sample Inference for Clustered Data , 2004 .

[164]  J. Hagenaars,et al.  Methods in Human Growth Research: Ordinal longitudinal data analysis , 2004 .

[165]  R. Byng,et al.  Exploratory cluster randomised controlled trial of shared care development for long-term mental illness. , 2004, The British journal of general practice : the journal of the Royal College of General Practitioners.

[166]  Ivy Liu.  The Analysis of Ordered Categorical Data : An Overview and a Survey of Recent Developments , 2005 .

[167]  W. Pan,et al.  Small‐sample performance of the robust score test and its modifications in generalized estimating equations , 2005, Statistics in medicine.

[168]  T. Banerjee,et al.  Fisher Information Matrix of the Dirichlet‐multinomial Distribution , 2005, Biometrical journal. Biometrische Zeitschrift.

[169]  P. Fayers,et al.  Determinants of the intracluster correlation coefficient in cluster randomized trials: the case of implementation research , 2005, Clinical trials.

[170]  G. Molenberghs,et al.  Models for Discrete Longitudinal Data , 2005 .

[171]  PQL Estimation Biases in Generalized Linear Mixed Models , 2005 .

[172]  S. Rabe-Hesketh,et al.  Maximum likelihood estimation of limited and discrete dependent variable models with nested random effects , 2005 .

[173]  J. Ward,et al.  Does 'peer coaching' increase GP capacity to promote informed decision making about PSA screening? A cluster randomised trial. , 2005, Family practice.

[174]  Xihong Lin,et al.  QUANTIFYING PQL BIAS IN ESTIMATING CLUSTER-LEVEL COVARIATE EFFECTS IN GENERALIZED LINEAR MIXED MODELS FOR GROUP-RANDOMIZED TRIALS , 2005 .

[175]  J. Williamson,et al.  Sample‐size calculations for studies with correlated ordinal outcomes , 2005, Statistics in medicine.

[176]  Allan Donner,et al.  Group sequential methods for cluster randomization trials with binary outcomes , 2005, Clinical trials.

[177]  A. Leon,et al.  A Comparison of Multiplicity Adjustment Strategies for Correlated Binary Endpoints , 2005, Journal of biopharmaceutical statistics.

[178]  D. Hedeker,et al.  A Mixed-eeects Regression Model for Three-level Ordinal Response Data , 2022 .

[179]  D. Ashby,et al.  Sample size for cluster randomized trials: effect of coefficient of variation of cluster size and analysis method. , 2006, International journal of epidemiology.

[180]  H. Demirtas.  A method for multivariate ordinal data generation given marginal distributions and correlations , 2006 .

[181]  J. Carlin,et al.  Promoting social inclusion in schools: a group-randomized trial of effects on student health risk behavior and well-being. , 2006, American journal of public health.

[182]  J. Pinheiro,et al.  Efficient Laplacian and Adaptive Gaussian Quadrature Algorithms for Multilevel Generalized Linear Mixed Models , 2006 .

[183]  R. Glynn,et al.  The Wilcoxon Signed Rank Test for Paired Comparisons of Clustered Data , 2006, Biometrics.

[184]  R. Glynn,et al.  Extension of the Rank Sum Test for Clustered Data: Two‐Group Comparisons with Group Membership Defined at the Subunit Level , 2006, Biometrics.

[185]  Patrick Royston,et al.  The design of simulation studies in medical statistics , 2006, Statistics in medicine.

[186]  B. Qaqish,et al.  A Comparison of Two Bias‐Corrected Covariance Estimators for Generalized Estimating Equations , 2007, Biometrics.

[187]  D. Schillinger,et al.  Physician notification of their diabetes patients’ limited health literacy: A randomized, controlled trial , 2007, Journal of General Internal Medicine.

[188]  Thomas D. Cook,et al.  Introduction to Statistical Methods for Clinical Trials , 2007 .

[189]  T. Tsou,et al.  Parametric robust inferences for correlated ordinal data , 2008, Statistics in medicine.

[190]  Jonathan L. Blitstein,et al.  Design and analysis of group-randomized trials in cancer: a review of current practices. , 2008, Journal of the National Cancer Institute.

[191]  Nick R. Parsons,et al.  Repeated measures proportional odds logistic regression analysis of ordinal score data in the statistical software package R , 2009, Comput. Stat. Data Anal..

[192]  Trend tests for genetic association using population-based cross-sectional complex survey data. , 2010, Biostatistics.

[193]  E. Waclawski.  Health Measurement Scales—A Practical Guide to Their Development and Use , 2010 .

[194]  S. Lipsitz,et al.  An extension of the Wilcoxon rank sum test for complex sample survey data , 2012, Journal of the Royal Statistical Society. Series C, Applied statistics.