NotesFAQContact Us
Collection
Advanced
Search Tips
Publication Date
In 20250
Since 20240
Since 2021 (last 5 years)0
Since 2016 (last 10 years)1
Since 2006 (last 20 years)7
Audience
Researchers1
Laws, Policies, & Programs
Assessments and Surveys
Cognitive Abilities Test1
What Works Clearinghouse Rating
Showing 1 to 15 of 18 results Save | Export
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Dogan, C. Deha – Eurasian Journal of Educational Research, 2017
Background: Most of the studies in academic journals use p values to represent statistical significance. However, this is not a good indicator of practical significance. Although confidence intervals provide information about the precision of point estimation, they are, unfortunately, rarely used. The infrequent use of confidence intervals might…
Descriptors: Sampling, Statistical Inference, Periodicals, Intervals
Spinella, Sarah – Online Submission, 2011
As result replicability is essential to science and difficult to achieve through external replicability, the present paper notes the insufficiency of null hypothesis statistical significance testing (NHSST) and explains the bootstrap as a plausible alternative, with a heuristic example to illustrate the bootstrap method. The bootstrap relies on…
Descriptors: Sampling, Statistical Inference, Statistical Significance, Error of Measurement
Peer reviewed Peer reviewed
PDF on ERIC Download full text
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
Peer reviewed Peer reviewed
Direct linkDirect link
Phillips, Gary W. – Applied Measurement in Education, 2015
This article proposes that sampling design effects have potentially huge unrecognized impacts on the results reported by large-scale district and state assessments in the United States. When design effects are unrecognized and unaccounted for they lead to underestimating the sampling error in item and test statistics. Underestimating the sampling…
Descriptors: State Programs, Sampling, Research Design, Error of Measurement
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Solanas, Antonio; Manolov, Rumen; Sierra, Vicenta – Psicologica: International Journal of Methodology and Experimental Psychology, 2010
In the first part of the study, nine estimators of the first-order autoregressive parameter are reviewed and a new estimator is proposed. The relationships and discrepancies between the estimators are discussed in order to achieve a clear differentiation. In the second part of the study, the precision in the estimation of autocorrelation is…
Descriptors: Computation, Hypothesis Testing, Correlation, Monte Carlo Methods
Peer reviewed Peer reviewed
Direct linkDirect link
Kim, Se-Kang – International Journal of Testing, 2010
The aim of the current study is to validate the invariance of major profile patterns derived from multidimensional scaling (MDS) by bootstrapping. Profile Analysis via Multidimensional Scaling (PAMS) was employed to obtain profiles and bootstrapping was used to construct the sampling distributions of the profile coordinates and the empirical…
Descriptors: Intervals, Multidimensional Scaling, Profiles, Evaluation
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Broughman, Stephen P.; Swaim, Nancy L.; Hryczaniuk, Cassie A. – National Center for Education Statistics, 2011
In 1988, the National Center for Education Statistics (NCES) introduced a proposal to develop a private school data collection that would improve on the sporadic collection of private school data dating back to 1890 and improve on commercially available private school sampling frames. Since 1989, the U.S. Bureau of the Census has conducted the…
Descriptors: Private Schools, Statistical Significance, Sampling, Statistics
Peer reviewed Peer reviewed
Carver, Ronald P. – Journal of Experimental Education, 1993
Four things are recommended to minimize the influence or importance of statistical significance testing. Researchers must not neglect to add "statistical" to significant and could interpret results before giving p-values. Effect sizes should be reported with measures of sampling error, and replication can be built into the design. (SLD)
Descriptors: Educational Researchers, Effect Size, Error of Measurement, Research Methodology
Peer reviewed Peer reviewed
Carroll, Robert M.; Nordholm, Lena A. – Educational and Psychological Measurement, 1975
Statistics used to estimate the population correlation ratio were reviewed and evaluated. The sampling distributions of Kelly's and Hays' statistics were studied empirically by computer simulation within the context of a three level one-way fixed effects analysis of variance design. (Author/RC)
Descriptors: Analysis of Variance, Bias, Comparative Analysis, Correlation
Peer reviewed Peer reviewed
Rasmussen, Jeffrey Lee – Evaluation Review, 1985
A recent study (Blair and Higgins, 1980) indicated a power advantage for the Wilcoxon W Test over student's t-test when calculated from a common mixed-normal sample. Results of the present study indicate that the t-test corrected for outliers shows a superior power curve to the Wilcoxon W.
Descriptors: Computer Simulation, Error of Measurement, Hypothesis Testing, Power (Statistics)
Helberg, Clay – 1996
Abuses and misuses of statistics are frequent. This digest attempts to warn against these in three broad classes of pitfalls: sources of bias, errors of methodology, and misinterpretation of results. Sources of bias are conditions or circumstances that affect the external validity of statistical results. In order for a researcher to make…
Descriptors: Causal Models, Comparative Analysis, Data Analysis, Error of Measurement
Vasu, Ellen S.; Elmore, Patricia B. – 1975
The effects of the violation of the assumption of normality coupled with the condition of multicollinearity upon the outcome of testing the hypothesis Beta equals zero in the two-predictor regression equation is investigated. A monte carlo approach was utilized in which three differenct distributions were sampled for two sample sizes over…
Descriptors: Correlation, Error of Measurement, Factor Structure, Hypothesis Testing
Harris, Chester W.; And Others – 1977
The implications of a mathematical model of test scores are explored where the data are limited to a random sample of items without replacement from an indefinitely large population or item domain in which items are scored either zero or one. The purpose is to obtain an unbiased estimate of a student's proportion of items correct in the item…
Descriptors: Academic Achievement, Achievement Tests, Annotated Bibliographies, Bibliographies
Vermillion, James E. – 1980
The presence of artifactual bias in analysis of covariance (ANCOVA) and in matching nonequivalent control group (NECG) designs was empirically investigated. The data set was obtained from a study of the effects of a television program on children from three day care centers in Mexico in which the subjects had been randomly selected within centers.…
Descriptors: Analysis of Covariance, Control Groups, Error of Measurement, Experimental Groups
Hart, Roland J.; Bradshaw, Stephen C. – 1981
This report provides the statistical tools necessary to measure the extent of error that exists in organizational record data and group survey data. It is felt that traditional methods of measuring error are inappropriate or incomplete when applied to organizational groups, especially in studies of organizational change when the same variables are…
Descriptors: Adults, Analysis of Variance, Error of Measurement, Mathematical Formulas
Previous Page | Next Page ยป
Pages: 1  |  2