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Braumoeller, Bear F. – Sociological Methods & Research, 2017
Fuzzy-set qualitative comparative analysis (fsQCA) has become one of the most prominent methods in the social sciences for capturing causal complexity, especially for scholars with small- and medium-"N" data sets. This research note explores two key assumptions in fsQCA's methodology for testing for necessary and sufficient…
Descriptors: Qualitative Research, Comparative Analysis, Social Science Research, Research Methodology
Bauer, Daniel J. – Psychometrika, 2009
When using linear models for cluster-correlated or longitudinal data, a common modeling practice is to begin by fitting a relatively simple model and then to increase the model complexity in steps. New predictors might be added to the model, or a more complex covariance structure might be specified for the observations. When fitting models for…
Descriptors: Goodness of Fit, Computation, Models, Predictor Variables
Tanaka, J. S. – 1981
Using Goodman's (1975) notion of quasi-independence as a method of obtaining goodness of fit measures for non-scalable types in a scalogram analysis, archival data sets were examined using available Guttman scaling techniques, recent developments in latent structure analysis, and multidimensional scaling procedures. The Stouffer-Toby (1951) data…
Descriptors: Goodness of Fit, Mathematical Models, Multidimensional Scaling, Rating Scales

van den Putte, Bas; Hoogstraten, Johan – Structural Equation Modeling, 1997
Problems found in the application of structural equation modeling to the theory of reasoned action are explored, and an alternative model specification is proposed that improves the fit of the data while leaving intact the structural part of the model being tested. Problems and the proposed alternative are illustrated. (SLD)
Descriptors: Goodness of Fit, Mathematical Models, Research Methodology, Structural Equation Models

Cliff, Norman – Multivariate Behavioral Research, 1983
The dangers of overlooking time-honored cautions in the making causal interpretations of data analyses from correlational studies when using highly sophisticated computer programs and their associated techniques are discussed. (JKS)
Descriptors: Computer Programs, Goodness of Fit, Mathematical Models, Multivariate Analysis

Tanaka, Jeffrey S. – Evaluation and Program Planning: An International Journal, 1982
Implications of model evaluation (using traditional chi square goodness of fit statistics, incremental fit indices for covariance structure models, and latent variable coefficients of determination) on substantive conclusions are illustrated with an example examining the effects of participation in a compensatory education program on posttreatment…
Descriptors: Cognitive Ability, Compensatory Education, Evaluation Criteria, Goodness of Fit

Nicholls, Paul Travis – Journal of the American Society for Information Science, 1989
Examines the elements involved in fitting a bibliometric model to empirical data, proposes a consistent methodology for applying Lotka's law, and presents the results of an empirical test of the methodology. The results are discussed in terms of the validity of Lotka's law and the suitability of the proposed methodology. (49 references) (CLB)
Descriptors: Bibliometrics, Data Analysis, Goodness of Fit, Mathematical Models

Johnson, Blair T.; Turco, Robin Maria – Communication Monographs, 1992
Recommends that analysts (1) use conventional meta-analytic statistics when testing for moderator variables; (2) perform tests between mean effect sizes; and (3) continue to perform model tests in meta-analyses for which study outcomes are already consistent if they have theoretical expectations about moderators. (RS)
Descriptors: Effect Size, Goodness of Fit, Mathematical Models, Meta Analysis

Velicer, Wayne F.; McDonald, Roderick P. – Multivariate Behavioral Research, 1984
A new approach to time series analysis was developed. It employs a generalized transformation of the observed data to meet the assumptions of the general linear model, thus eliminating the need to identify a specific model. This approach permits alternative computational procedures, based on a generalized least squares algorithm. (Author/BW)
Descriptors: Goodness of Fit, Least Squares Statistics, Mathematical Models, Research Design

MacCallum, Robert C. – Psychometrika, 1976
Concerned with consequences of employing the INDSCAL model when one of its assumptions are known to be violated. Under study is the notion that all individuals perceive the object space dimensions to be independent. (RC)
Descriptors: Factor Analysis, Goodness of Fit, Individual Differences, Mathematical Models

Holt, D. – Sociological Methods and Research, 1979
Two techniques for interpretation of fitted log-linear models in contingency table analysis are discussed. The use of odds ratios as opposed to direct interpretation of the fitted model is argued for. (Author/JKS)
Descriptors: Expectancy Tables, Goodness of Fit, Hypothesis Testing, Mathematical Models

Joreskog, K. G. – Psychometrika, 1971
Considers the study of similarities and differences in factor structures between different groups. (AG)
Descriptors: Computer Programs, Factor Analysis, Goodness of Fit, Hypothesis Testing

Hedges, Larry V. – Journal of Educational Statistics, 1982
Quantitative methods for research synthesis usually involve calculation of an estimate of effect size for each of a series of studies. Some problems associated with ad hoc methods of analysis, such as ordinary least squares regression analysis using estimates of effect size, are described. (Author/JKS)
Descriptors: Estimation (Mathematics), Goodness of Fit, Least Squares Statistics, Mathematical Models
Keats, John B.; Brewer, James K. – 1971
This paper presents an index of goodness-of-fit for comparing m models over n trials. The index allows for differentiated weighting of the trials as to their importance in the comparison of the models. Several possible weighting schemes are suggested and the conditions on the weights which assure asymptotic normality of the index distribution are…
Descriptors: Goodness of Fit, Hypothesis Testing, Mathematical Models, Nonparametric Statistics
Linacre, John M. – 1989
A Rasch measurement model can be constructed to meet the requirements of rank ordered data. If multiple rankings of the same objects are available, then the parameters of the objects can be estimated, along with their standard errors and also with statistics summarizing the fit of the data to the measurement model. This paper summarizes the…
Descriptors: Data Analysis, Equations (Mathematics), Error of Measurement, Goodness of Fit