Descriptor
| Hypothesis Testing | 3 |
| Power (Statistics) | 3 |
| Predictor Variables | 3 |
| Research Design | 2 |
| Sample Size | 2 |
| Sampling | 2 |
| Correlation | 1 |
| Effect Size | 1 |
| Equations (Mathematics) | 1 |
| Estimation (Mathematics) | 1 |
| Experimental Groups | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 2 |
| Reports - Evaluative | 2 |
| Reports - Research | 1 |
| Speeches/Meeting Papers | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewedChan, Wai; Yung, Yiu-Fai; Bentler, Peter M.; Tang, Man-Lai – Educational and Psychological Measurement, 1998
Two bootstrap tests are proposed to test the independence hypothesis in a two-way cross table. Monte Carlo studies are used to compare the traditional asymptotic test with these bootstrap methods, and the bootstrap methods are found superior in two ways: control of Type I error and statistical power. (SLD)
Descriptors: Hypothesis Testing, Monte Carlo Methods, Power (Statistics), Predictor Variables
Maxwell, Scott E. – 1979
Arguments have recently been put forth that standard textbook procedures for determining the sample size necessary to achieve a certain level of power in a completely randomized design are incorrect when the dependent variable is fallible because they ignore measurement error. In fact, however, there are several correct procedures, one of which is…
Descriptors: Hypothesis Testing, Mathematical Formulas, Power (Statistics), Predictor Variables
Peer reviewedGreen, Samuel B. – Multivariate Behavioral Research, 1991
An evaluation of the rules-of-thumb used to determine the minimum number of subjects required to conduct multiple regression analyses suggests that researchers who use a rule of thumb rather than power analyses trade simplicity of use for accuracy and specificity of response. Insufficient power is likely to result. (SLD)
Descriptors: Correlation, Effect Size, Equations (Mathematics), Estimation (Mathematics)


