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Vaske, Jerry J. – Sagamore-Venture, 2019
Data collected from surveys can result in hundreds of variables and thousands of respondents. This implies that time and energy must be devoted to (a) carefully entering the data into a database, (b) running preliminary analyses to identify any problems (e.g., missing data, potential outliers), (c) checking the reliability and validity of the…
Descriptors: Surveys, Theories, Hypothesis Testing, Effect Size
Huang, Francis L. – Educational and Psychological Measurement, 2018
Cluster randomized trials involving participants nested within intact treatment and control groups are commonly performed in various educational, psychological, and biomedical studies. However, recruiting and retaining intact groups present various practical, financial, and logistical challenges to evaluators and often, cluster randomized trials…
Descriptors: Multivariate Analysis, Sampling, Statistical Inference, Data Analysis
Finch, W. Holmes – Journal of Experimental Education, 2016
Multivariate analysis of variance (MANOVA) is widely used in educational research to compare means on multiple dependent variables across groups. Researchers faced with the problem of missing data often use multiple imputation of values in place of the missing observations. This study compares the performance of 2 methods for combining p values in…
Descriptors: Multivariate Analysis, Educational Research, Error of Measurement, Research Problems
Warne, Russell T.; Li, Yan; McKyer, E. Lisako J.; Condie, Rachel; Diep, Cassandra S.; Murano, Peter S. – Journal of Nutrition Education and Behavior, 2012
Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence…
Descriptors: Nutrition, Statistical Analysis, Sampling, Research
Citkowicz, Martyna; Hedges, Larry V. – Society for Research on Educational Effectiveness, 2013
In some instances, intentionally or not, study designs are such that there is clustering in one group but not in the other. This paper describes methods for computing effect size estimates and their variances when there is clustering in only one group and the analysis has not taken that clustering into account. The authors provide the effect size…
Descriptors: Multivariate Analysis, Effect Size, Sampling, Sample Size
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
Keaton, Shaughan A.; Bodie, Graham D. – International Journal of Listening, 2013
This article investigates the quality of social scientific listening research that reports numerical data to substantiate claims appearing in the "International Journal of Listening" between 1987 and 2011. Of the 225 published articles, 100 included one or more studies reporting numerical data. We frame our results in terms of eight…
Descriptors: Periodicals, Journal Articles, Listening, Social Science Research
Ruscio, John; Kaczetow, Walter – Multivariate Behavioral Research, 2008
Simulating multivariate nonnormal data with specified correlation matrices is difficult. One especially popular method is Vale and Maurelli's (1983) extension of Fleishman's (1978) polynomial transformation technique to multivariate applications. This requires the specification of distributional moments and the calculation of an intermediate…
Descriptors: Monte Carlo Methods, Correlation, Sampling, Multivariate Analysis
Hahs-Vaughn, Debbie L. – International Journal of Research & Method in Education, 2006
Oversampling and cluster sampling must be addressed when analyzing complex sample data. This study: (a) compares parameter estimates when applying weights versus not applying weights; (b) examines subset selection issues; (c) compares results when using standard statistical software (SPSS) versus specialized software (AM); and (d) offers…
Descriptors: Multivariate Analysis, Sampling, Data Analysis, Error of Measurement