TY  - BOOK
AU  - Gueorguieva,Ralitza
TI  - Statistical methods in psychiatry and related fields: longitudinal, clustered, and other repeated measures data 
SN  - 9781315151526
AV  - RC337 .G87 2018
U1  - 616.8900727 
PY  - 2018///]
CY  - Boca Raton, Florida
PB  - CRC Press
KW  - Psychiatry
KW  - Research
KW  - Statistical methods
N1  - chapter Introduction;  Gueorguieva Ralitza --; chapter Traditional Methods for Analysis of Longitudinal and Clustered Data;  Gueorguieva Ralitza --; chapter Linear Mixed Models for Longitudinal and Clustered Data;  Gueorguieva Ralitza --; chapter Linear Models for Non-Normal Outcomes;  Gueorguieva Ralitza --; chapter Non-Parametric Methods for the Analysis of Repeatedly Measured Data;  Gueorguieva Ralitza --; chapter Post Hoc Analysis and Adjustments for Multiple Comparisons;  Gueorguieva Ralitza --; chapter Handling of Missing Data and Dropout in Longitudinal Studies;  Gueorguieva Ralitza --; chapter Controlling for Covariates in Studies with Repeated Measures;  Gueorguieva Ralitza --; chapter Assessment of Moderator and Mediator Effects;  Gueorguieva Ralitza --; chapter Mixture Models for Trajectory Analyses;  Gueorguieva Ralitza --; chapter Study Design and Sample Size Calculations;  Gueorguieva Ralitza --; chapter Summary and Further Readings;  Gueorguieva Ralitza
N2  - "Data collected in psychiatry and related fields are complex because outcomes are rarely directly observed, there are multiple correlated repeated measures within individuals, there is natural heterogeneity in treatment responses and in other characteristics in the populations. Simple statistical methods do not work well with such data. More advanced statistical methods capture the data complexity better, but are difficult to apply appropriately and correctly by investigators who do not have advanced training in statistics. This book presents, at a non-technical level, several approaches for the analysis of correlated data: mixed models for continuous and categorical outcomes, nonparametric methods for repeated measures and growth mixture models for heterogeneous trajectories over time. Separate chapters are devoted to techniques for multiple comparison correction, analysis in the presence of missing data, adjustment for covariates, assessment of mediator and moderator effects, study design and sample size considerations. The focus is on the assumptions of each method, applicability and interpretation rather than on technical details. The intended audience are applied researchers with minimal knowledge of statistics, although the book could also benefit collaborating statisticians. The book, together with the online materials, is a valuable resource aimed at promoting the use of appropriate statistical methods for the analysis of repeated measures data. "--Provided by publisher
UR  - https://www.taylorfrancis.com/books/9781315151526
ER  -