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Beaujean, A. Alexander – Practical Assessment, Research & Evaluation, 2014
A common question asked by researchers using regression models is, What sample size is needed for my study? While there are formulae to estimate sample sizes, their assumptions are often not met in the collected data. A more realistic approach to sample size determination requires more information such as the model of interest, strength of the…
Descriptors: Regression (Statistics), Sample Size, Sampling, Monte Carlo Methods
Yagiz, Oktay; Aydin, Burcu; Akdemir, Ahmet Selçuk – Journal of Language and Linguistic Studies, 2016
This study reviews a selected sample of 274 research articles on ELT, published between 2005 and 2015 in Turkish contexts. In the study, 15 journals in ULAKBIM database and articles from national and international journals accessed according to convenience sampling method were surveyed and relevant articles were obtained. A content analysis was…
Descriptors: Journal Articles, Periodicals, Content Analysis, Research Design
Schoenfeld, Daniel – ProQuest LLC, 2011
The current study addressed some of the methodological shortcomings of previous studies on internet addiction. The main purpose of the study was to determine if two different internet addiction assessments would identify the same individuals as addicted to the internet. A total of 224 undergraduate internet users were surveyed using a stratified…
Descriptors: Internet, Addictive Behavior, Undergraduate Students, Correlation
Bailey, Brad; Spence, Dianna J.; Sinn, Robb – Journal of Statistics Education, 2013
Researchers and statistics educators consistently suggest that students will learn statistics more effectively by conducting projects through which they actively engage in a broad spectrum of tasks integral to statistical inquiry, in the authentic context of a real-world application. In keeping with these findings, we share an implementation of…
Descriptors: Statistics, Curriculum Implementation, Discovery Learning, Learning Activities
Moerbeek, Mirjam – Journal of Educational and Behavioral Statistics, 2008
Three issues need to be decided in the design stage of a longitudinal intervention study: the number of persons, the number of repeated measurements per person, and the duration of the study. The degree to which polynomial effects vary across persons and the drop-out pattern also influence the statistical power to detect intervention effects. This…
Descriptors: Intervention, Sample Size, Research Methodology, Longitudinal Studies
Rijmen, Frank; Vansteelandt, Kristof; De Boeck, Paul – Psychometrika, 2008
The increasing use of diary methods calls for the development of appropriate statistical methods. For the resulting panel data, latent Markov models can be used to model both individual differences and temporal dynamics. The computational burden associated with these models can be overcome by exploiting the conditional independence relations…
Descriptors: Markov Processes, Patients, Regression (Statistics), Probability
Ozechowski, Timothy J.; Turner, Charles W.; Hops, Hyman – Psychological Methods, 2007
This article demonstrates the use of mixed-effects logistic regression (MLR) for conducting sequential analyses of binary observational data. MLR is a special case of the mixed-effects logit modeling framework, which may be applied to multicategorical observational data. The MLR approach is motivated in part by G. A. Dagne, G. W. Howe, C. H.…
Descriptors: Probability, Young Adults, Sampling, Observation
Propensity Score Matching Strategies for Evaluating the Success of Child and Family Service Programs
Barth, Richard P.; Guo, Shenyang; McCrae, Julie S. – Research on Social Work Practice, 2008
This article presents propensity score matching as a method to implement randomized conditions to analyze service effects using nonexperimental data. Most social work research is challenged to implement randomized clinical trials, whereas administrative and survey data are often available and can provide valuable information about services…
Descriptors: Research Methodology, Social Work, Scores, Evaluation Methods
Witta, Lea; Kaiser, Javaid – 1991
When survey data are statistically analyzed, many times some of the data is missing. If the missing values are not correctly handled, results of the analysis may be dubious and publication may jeopardize the credibility of the organization preparing the report. This study examined four of the more commonly used methods of handling missing data.…
Descriptors: Comparative Analysis, Evaluation Methods, Predictive Measurement, Regression (Statistics)
Thompson, Bruce – 1995
Stepwise methods are frequently employed in educational and psychological research, both to select useful subsets of variables and to evaluate the order of importance of variables. Three problems with stepwise applications are explored in some detail. First, computer packages use incorrect degrees of freedom in their stepwise computations,…
Descriptors: Educational Research, Error of Measurement, Heuristics, Psychological Testing
Thompson, Bruce – 1992
Three criticisms of overreliance on results from statistical significance tests are noted. It is suggested that: (1) statistical significance tests are often tautological; (2) some uses can involve comparisons that are not completely sensible; and (3) using statistical significance tests to evaluate both methodological assumptions (e.g., the…
Descriptors: Effect Size, Estimation (Mathematics), Evaluation Methods, Regression (Statistics)
Beaton, Albert E. – 1981
Least squares fitting process as a method of data reduction is presented. The general strategy is to consider fitting (linear) models as partitioning data into a fit and residuals. The fit can be parsimoniously represented by a summary of the data. A fit is considered adequate if the residuals are small enough so that manipulating their signs and…
Descriptors: Goodness of Fit, Least Squares Statistics, Mathematical Models, Measurement Techniques
Thompson, Bruce – 1992
Conventional statistical significance tests do not inform the researcher regarding the likelihood that results will replicate. One strategy for evaluating result replication is to use a "bootstrap" resampling of a study's data so that the stability of results across numerous configurations of the subjects can be explored. This paper…
Descriptors: Analysis of Covariance, Analysis of Variance, Correlation, Discriminant Analysis
Lunneborg, Clifford E. – 1983
The wide availability of large amounts of inexpensive computing power has encouraged statisticians to explore many approaches to a basis for inference. This paper presents one such "computer-intensive" approach: the bootstrap of Bradley Efron. This methodology fits between the cases where it is assumed that the form of the distribution…
Descriptors: Analysis of Variance, Error of Measurement, Estimation (Mathematics), Hypothesis Testing
Howell-White, Sandra; Gaboda, Dorothy; Rosato, Nancy Scotto; Lucas, Judith A. – Gerontologist, 2006
Purpose: This research provides state policy makers and others interested in developing needs-based reimbursement models for Medicaid-funded assisted living with an evaluation of different methodologies that affect the structure and outcomes of these models. Design and Methods: We used assessment data from Medicaid-enrolled assisted living…
Descriptors: Models, Statistical Analysis, Individual Characteristics, Health Services
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