This work describes the mathematical and logical foundations at a level which does not presume advanced mathematical or statistical skills, illustrating how to do factor analysis with several of the more popular packaged computer programmes.

Describes various commonly used methods of initial factoring and factor rotation. In addition to a full discussion of exploratory factor analysis, confirmatory factor analysis and various methods of constructing factor scales are also presented.

A presentation and critique of the use of multiple measures of theoretical concepts for the assessment of validity (using the multi-trait multi-method matrix) and reliability (using multiple indicators with a path analytic framework).

An introduction to the underlying principles, central concepts, and basic techniques for conducting and understanding exploratory data analysis -- with numerous social science examples.

Explains how social scientists can evaluate the reliability and validity of empirical measurements, discussing the three basic types of validity: criterion related, content, and construct. In addition, the paper shows how reliability is assessed by the retest method, alternative-forms procedure, split-halves approach, and internal consistency method.

An introduction to a variety of techniques that may be used in the analysis of data from a panel study -- information obtained from a large number of entities at two or more points in time. The focus of this volume is on analysis rather than problems of sampling or design, and its emphasis is on application rather than theory.

These procedures, collectively known as discriminant analysis, allow a researcher to study the difference between two or more groups of objects with respect to several variables simultaneously, determining whether meaningful differences exist between the groups and identifying the discriminating power of each variable.

Describes ARIMA or Box Tiao models, widely used in the analysis of interupted time series quasi-experiments, assuming no statistical background beyond simple correlation. The principles and concepts of ARIMA time series analyses are developed and applied where a discrete intervention has impacted a social system.

'...this is the kind of exposition I wished I had had some ten years ago when venturing into the world of autoregressive, moving-average (ARIMA) models of time-series analysis...This monograph nicely lays out a method for assessing the impact of a discrete policy or event of some...

Research Designs is a clear, compact introduction to the principles of experimental and non-experimental design -- especially written for social scientists and their students. Spector covers major designs including: single group designs; pre-test/post-test designs; factorial designs, hierarchical designs; multivariate designs; the Solomon four group design; panel designs; and designs with concomitant variables. 'Bearing in mind the brevity (and hence cheapness) of the book, its coverage is extremely wide-ranging...As long as a basic grounding is achieved beforehand, attending to Spector's...