Tarling, Roger, <br/><br/>
Statistical modelling for social researchers :  principles and practice / 
Roger Tarling. 
 - x, 210 pages :  illustrations, plans ;  26 cm. 
 - Social research today .
 - Social research today (Routledge (Firm)). .
<br/><br/>Includes bibliographical references and index. 
<br/><br/> Statistical modelling: An overview --  Research designs and data --  Statistical preliminaries --  Multiple regression for continuous response variables --  Logistic regression for binary response variables --  Multinomial logistic regression for multinomial response variables --  Loglinear models --  Ordinal logistic regression for ordered categorical response variables --  Multilevel modelling --  Latent variables and factor analysis --  Causal modelling: simultaneous equation models --  Longitudinal data analysis --  Event history models --  The generalised linear model --  Handling tabular data.  1.  2.  3.  4.  5.  6.  7.  8.  9.  10.  11.  12.  13.  Appendix 1.  Appendix 2. 
<br/><br/> "This book explains the principles and theory of statistical modelling in an intelligible way for the non-mathematical social scientist looking to apply statistical modelling techniques in research. The book also serves as an introduction for those wishing to develop more detailed knowledge and skills in statistical modelling. Rather than present a limited number of statistical models in great depth, the aim is to provide a comprehensive overview of the statistical models currently adopted in social research, in order that the researcher can make appropriate choices and select the most suitable model for the research question to be addressed. To facilitate application, the book also offers practical guidance and instruction in fitting models using SPSS and Stata, the most popular statistical computer software which is available to most social researchers. Instruction in using MLwiN is also given. Models covered in the book include; multiple regression, binary, multinomial and ordered logistic regression, log-linear models, multilevel models, latent variable models (factor analysis), path analysis and simultaneous equation models and models for longitudinal data and event histories. An accompanying website hosts the datasets and further exercises in order that the reader may practice developing statistical models."--Publisher's website. 
<br/><br/><label>ISBN: </label>0415448379 9780415448376 0415448409 9780415448406 
<br/><br/><label>LCCN: </label>2008008888 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Social sciences--Research--Statistical methods.<br/>Social sciences--Statistical methods.
<br/><br/><label>LC Class. No.: </label>HA29  / .T28 2009 
<br/><br/><label>Dewey Class. No.: </label>519.5