When conducting an exploratory factor analysis, the decision regarding the number of factors to retain following factor extraction is one that the researcher should consider very carefully, as the decision can have a dramatic effect on results. Although there are numerous strategies that can and should be utilized when making this decision,…

The use of the 2 x 2 matrix in qualitative data analysis and theory generation is discussed, embracing the perspective that the objective of qualitative research in general and the analysis of qualitative data in particular is the development of theory. A 2 x 2 matrix is considered to be a tabular representation of the relationship of two…

Based on preliminary interviews with 40 adults, an instrument was devised for assessing voters' uses and gratifications of viewing television news about presidential campaigns. When this instrument was used to survey 226 persons of voting age, an analysis by orthogonal rotation of the data produced a six-factor solution accounting for 52.6% of the…

With the advent of the computer and user-friendly statistical software packages, factor analysis has become accessible to most researchers. However, conventional factor analysis, or R-technique, is only useful for research concerning types or groups of variables. Educational and psychological researchers are often interested in types of people,…

This paper discusses the theoretical scope and practical applicability of generalizability (G) theory through the principle of symmetry. Major ideas are summarized and factors hindering applications of G theory in research conducted in French-speaking Europe are presented. The principle of symmetry affirms that any factor of a design can be…

New ways of using factor analysis in research designs are suggested in this paper that would allow research to move in new directions that are being suggested for educational technology. A brief simplified overview of factor-analytic techniques is given, followed by a description of some recent developments in factor-analytic techniques which make…

The basic considerations that should be examined in performing an exploratory descriptive factor analysis of a communication concept are described in this paper. Factor analysis is a statistical technique designed to identify the fundamental, common elements within a pool of variables. For example, imagine asking students twenty questions all…

A common problem in the behavioral sciences is to determine if a set of observed variables can be more parsimoniously represented by a smaller set of derived variables. To address this problem, the performance of five methods for determining the number of components to retain (Horn's parallel analysis, Velicer's Minimum Average Partial (MAP),…

A study was undertaken to identify the factor structure of a battery of readiness measures and to demonstrate the concurrent and predictive validity of one instrument in that battery--the Pre-Reading Screening Procedures (PSP). Concurrent validity was determined by examining the correlation of the PSP with the Metropolitan Readiness Test (MRT),…

Ego development data were collected from two groups of subjects. One group consisted of 175 students from junior high, senior high, and college. The second group was comprised of 136 adults who were either teachers and administrators of a medium-sized public school system, or long-time employees of a large chemical manufacturing corporation.…

The hierarchical clustering technique was used to differentiate college dropouts from persisters, and to determine how student clusters differ from one another on relevant outcome variables. Subjects were 618 freshmen who entered a community college with the intention of completing a two-year associate degree. There were 432 persisters who…

Data reduction techniques seek to combine variables that account for patterns of variation in observed dependent variables in such a way that a simpler model is available for analysis. Factor analysis is a data reduction technique that attempts to model or explain a set of variables in terms of their associations. To understand why this technique…

The central objective of factor analysis is to explain the greatest amount of variance in a data set with the smallest number of factors. Higher-order analysis is an invaluable tool that offers the benefit of parsimony provided by first-order analysis with the opportunity to make data-based generalizations beyond the first-order. Higher-order…

A "doubly-centered" raw data matrix is one for which both columns and rows have both unit variance and means equal to zero. The factor scores from one analysis are the same as factor pattern coefficients from the other analysis except for a variance adjustment. This study explored an extension of the reciprocity principle which may have…

Q-type factor analysis was used to re-analyze baseline data collected in 1957, on 47 men aged 65-91. Q-type analysis is the use of factor methods to study persons rather than tests. Although 550 variables were originally studied involving psychiatry, medicine, cerebral metabolism and chemistry, personality, audiometry, dichotic and diotic memory,…