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Chattoe-Brown, Edmund – International Journal of Social Research Methodology, 2021
This article demonstrates how a technique called Agent-Based Modelling can address a significant challenge for effective interdisciplinarity. Different disciplines and research methods make divergent assertions about what a satisfactory explanation requires. However, without a unified framework analysing the implications of these differences…
Descriptors: Interdisciplinary Approach, Models, Research Methodology, Statistical Analysis
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Neale, Dave – Oxford Review of Education, 2015
Recently, Stephen Gorard has outlined strong objections to the use of significance testing in social research. He has argued, first, that as the samples used in social research are almost always non-random it is not possible to use inferential statistical techniques and, second, that even if a truly random sample were achieved, the logic behind…
Descriptors: Statistical Significance, Statistical Analysis, Sampling, Probability
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Cooper, Barry; Glaesser, Judith – International Journal of Social Research Methodology, 2016
Ragin's Qualitative Comparative Analysis (QCA) is often used with small to medium samples where the researcher has good case knowledge. Employing it to analyse large survey datasets, without in-depth case knowledge, raises new challenges. We present ways of addressing these challenges. We first report a single QCA result from a configurational…
Descriptors: Social Science Research, Robustness (Statistics), Educational Sociology, Comparative Analysis
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Bishara, Anthony J.; Hittner, James B. – Educational and Psychological Measurement, 2015
It is more common for educational and psychological data to be nonnormal than to be approximately normal. This tendency may lead to bias and error in point estimates of the Pearson correlation coefficient. In a series of Monte Carlo simulations, the Pearson correlation was examined under conditions of normal and nonnormal data, and it was compared…
Descriptors: Research Methodology, Monte Carlo Methods, Correlation, Simulation
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Pohl, Steffi; Steiner, Peter M.; Eisermann, Jens; Soellner, Renate; Cook, Thomas D. – Educational Evaluation and Policy Analysis, 2009
Adjustment methods such as propensity scores and analysis of covariance are often used for estimating treatment effects in nonexperimental data. Shadish, Clark, and Steiner used a within-study comparison to test how well these adjustments work in practice. They randomly assigned participating students to a randomized or nonrandomized experiment.…
Descriptors: Statistical Analysis, Social Science Research, Statistical Bias, Statistical Inference
Rosenthal, James A. – Springer, 2011
Written by a social worker for social work students, this is a nuts and bolts guide to statistics that presents complex calculations and concepts in clear, easy-to-understand language. It includes numerous examples, data sets, and issues that students will encounter in social work practice. The first section introduces basic concepts and terms to…
Descriptors: Statistics, Data Interpretation, Social Work, Social Science Research
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Yuan, Ke-Hai; Lambert, Paul L.; Fouladi, Rachel T. – Multivariate Behavioral Research, 2004
Mardia's measure of multivariate kurtosis has been implemented in many statistical packages commonly used by social scientists. It provides important information on whether a commonly used multivariate procedure is appropriate for inference. Many statistical packages also have options for missing data. However, there is no procedure for applying…
Descriptors: Social Science Research, Research Methodology, Statistical Distributions, Statistical Analysis
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Dimitrova, Ganka; And Others – Teaching Sociology, 1993
Describes the background, development, and testing of a computer software program designed to teach principles of statistical sampling in social science courses. Compares results of a field test of the program, Introduction to Sampling Error Experiments (ISEE), with traditional instruction. (CFR)
Descriptors: Computer Software, Computer Uses in Education, Curriculum Design, Educational Strategies
Rice, Marti H.; Stallings, William M. – 1986
This paper presents an overview of Florence Nightingale's statistical background and accomplishments; discusses Victorian statistics, Nightingale's education and statistical contributions; and concludes with implications for professors and students of educational research. Florence Nightingale (1820-1910), the first woman elected as a fellow of…
Descriptors: Adults, Biographies, Educational Researchers, Field Studies