Further Cross-Validation Analysis of the Bayesian m -Group Regression Method
Bibliographic Data
| ID | 8224465 |
|---|---|
| Authors | Melvin R Novick (American College Testing Program, corresponding author), Paul H Jackson (University College of Wales, Aberystwyth) |
| Year | 1974 |
| Volume | 11 |
| Issue | 1 |
| Pages | 77-85 |
| Publication date | 1974-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | American Educational Research Journal (JOURNAL) |
| Journal identifiers | ISSN: 0002-8312 • E-ISSN: 1935-1011 |
| Publisher | American Educational Research Association (AERA) (PUBLISHER) |
| DOI | 10.3102/00028312011001077 |
| OpenAlex | W2078552791 |
| Language | EN |
| Citations received | 1 |
| References cited | 11 |
Novick, Jackson, Thayer, and Cole (1972) conducted a cross-validation study of the Bayesian m-group regression method developed by Jackson, Novick, and Thayer (1971) based on a theory described in Lindley and Smith (1972). The context of this cross validation was the use of ACT Assessment Scores to predict first semester grade point averages in traditional junior colleges. Within-group least squares regression lines were calculated in each of 22 carefully selected, academically oriented junior colleges using 1968 data and these lines were used for prediction on 1969 data. The principal focus of accuracy of prediction was on the average over colleges of the mean-squared errors when the predictions for persons were compared with their actual attained grade point averages. The primary conclusions of the study were based on a 25% within-college sample. The sample sizes ranged from 26 to 184. The average, over the 22 colleges, of the mean-squared errors for the within-college regression was .62. This represents the average result to be expected if each college did its own work using only information from that college. There has always been the thought that some improvement on withincollege least squares could be attained by some central prediction system. However, we are unaware of a single example in the literature where a large scale cross-validation study has substantially supported this contention. In the instances we know of, cross validation has either not been done, has not been done successfully, or has not been done on a sufficient scale to clearly establish the general validity of the system used. We assume that there have
Context (archaeology · Cross-validation · Linear regression · Mean squared error · Regression · Regression analysis · Sample (material · Scale (ratio · Statistics · Advanced Statistical Methods and Models · Mathematics · Psychology
| Unique citing works | 1 |
|---|---|
| Citations per year | 0,02 |
| Citation span | 1974 - 1974 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 1 |