Discussion of "on State Education Statistics": A Difficulty with Regression Analyses of Regional Test Score Averages

1985 ◽  
Vol 10 (4) ◽  
pp. 326 ◽  
Author(s):  
Paul R. Rosenbaum ◽  
Donald B. Rubin
1985 ◽  
Vol 10 (4) ◽  
pp. 326-333 ◽  
Author(s):  
Paul R. Rosenbaum ◽  
Donald B. Rubin

The Department of Education’s table “State Education Statistics” reports mean test scores by state and mean resource inputs by state. The means are calculated from quite different groups of students, a process we call inconsistent aggregation. We investigate the bias in regression coefficients caused by inconsistent aggregation, first using theoretical calculations, and then by artificially aggregating data from the High School and Beyond sample.


1984 ◽  
Vol 1984 (1) ◽  
pp. i-86 ◽  
Author(s):  
Howard Wainer ◽  
Paul R. Rosenbaum ◽  
Spencer Swinton ◽  
Minhwei Wang

1985 ◽  
Vol 10 (4) ◽  
pp. 293 ◽  
Author(s):  
Howard Wainer ◽  
Paul W. Holland ◽  
Spencer Swinton ◽  
Min Hwei Wang

1994 ◽  
Vol 78 (3) ◽  
pp. 819-823 ◽  
Author(s):  
Donald J. Goldstein ◽  
Thomas W., Britt

Previous research on the relationship between visual-motor coordination and academic achievement has been equivocal and has frequently not included controls for the effect of intelligence on achievement. In the present study, scores on three tests of children's visual-motor coordination correlated moderately to highly with scores on a test of reading, mathematics, and written language for a sample of 44 elementary school children referred for learning difficulties. Multiple regression analyses indicated that visual-motor coordination scores accounted for little unique achievement test score variance when IQs were included in the equations.


1988 ◽  
Vol 10 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Alan L. Ginsburg ◽  
Jay Noell ◽  
Valena White Plisko

In 1984 the wall chart of State Education Statistics broke the historic silence on reporting state-by-state comparisons of student performance. Prior to its release, chief state school officers and the education establishment had been protected from disclosure of poor performance by the states in education. The wall chart, by laying out the facts in straightforward detail, exposed our national shortcomings in education and focused attention on the states where much of education policymaking takes place. This article reports on the history of the wall chart, addresses the criticisms that followed its release, and assesses its impact. It goes on to propose recommendations for improving the usefulness of state-by-state rankings. The insights it offers on designing state education comparisons may be particularly helpful as the nation and states undertake the expansion of the National Assessment of Educational Progress to report on student performance at the state level.


1970 ◽  
Vol 31 (3) ◽  
pp. 933-934
Author(s):  
Joanne Thorpe ◽  
Charlotte West

73 Ss were ranked on skill by means of a ladder tournament in badminton. Regression analyses indicated the game sense test score was not effective in predicting rank on the ladder tournament. Intercorrelations of the 10 subtests of the game sense test ranged from –.01 to .67 but were generally nonsignificant. The game sense test was invalid by the approach utilized.


1985 ◽  
Vol 10 (4) ◽  
pp. 293-325 ◽  
Author(s):  
Howard Wainer ◽  
Paul W. Holland ◽  
Spencer Swinton ◽  
Min Hwei Wang

In January 1984 and again in January 1985, then Secretary of Education Bell released the table “State Education Statistics.” These tables contained a variety of education indicators, among them average SAT or ACT scores for each state. In this paper we examine these scores to see if they can be used for state-by-state comparisons to aid in the evaluation of those educational policies that vary across states. We conclude that statistical adjustment to remove the bias introduced by inappropriate aggregation and self-selection of examinees is not sufficient to insure the validity of the kinds of inferences that are desired.


2020 ◽  
Vol 51 (3) ◽  
pp. 807-820
Author(s):  
Lena G. Caesar ◽  
Marie Kerins

Purpose The purpose of this study was to investigate the relationship between oral language, literacy skills, age, and dialect density (DD) of African American children residing in two different geographical regions of the United States (East Coast and Midwest). Method Data were obtained from 64 African American school-age children between the ages of 7 and 12 years from two geographic regions. Children were assessed using a combination of standardized tests and narrative samples elicited from wordless picture books. Bivariate correlation and multiple regression analyses were used to determine relationships to and relative contributions of oral language, literacy, age, and geographic region to DD. Results Results of correlation analyses demonstrated a negative relationship between DD measures and children's literacy skills. Age-related findings between geographic regions indicated that the younger sample from the Midwest outscored the East Coast sample in reading comprehension and sentence complexity. Multiple regression analyses identified five variables (i.e., geographic region, age, mean length of utterance in morphemes, reading fluency, and phonological awareness) that accounted for 31% of the variance of children's DD—with geographic region emerging as the strongest predictor. Conclusions As in previous studies, the current study found an inverse relationship between DD and several literacy measures. Importantly, geographic region emerged as a strong predictor of DD. This finding highlights the need for a further study that goes beyond the mere description of relationships to comparing geographic regions and specifically focusing on racial composition, poverty, and school success measures through direct data collection.


2020 ◽  
Vol 63 (7) ◽  
pp. 2281-2292
Author(s):  
Ying Zhao ◽  
Xinchun Wu ◽  
Hongjun Chen ◽  
Peng Sun ◽  
Ruibo Xie ◽  
...  

Purpose This exploratory study aimed to investigate the potential impact of sentence-level comprehension and sentence-level fluency on passage comprehension of deaf students in elementary school. Method A total of 159 deaf students, 65 students ( M age = 13.46 years) in Grades 3 and 4 and 94 students ( M age = 14.95 years) in Grades 5 and 6, were assessed for nonverbal intelligence, vocabulary knowledge, sentence-level comprehension, sentence-level fluency, and passage comprehension. Group differences were examined using t tests, whereas the predictive and mediating mechanisms were examined using regression modeling. Results The regression analyses showed that the effect of sentence-level comprehension on passage comprehension was not significant, whereas sentence-level fluency was an independent predictor in Grades 3–4. Sentence-level comprehension and fluency contributed significant variance to passage comprehension in Grades 5–6. Sentence-level fluency fully mediated the influence of sentence-level comprehension on passage comprehension in Grades 3–4, playing a partial mediating role in Grades 5–6. Conclusions The relative contributions of sentence-level comprehension and fluency to deaf students' passage comprehension varied, and sentence-level fluency mediated the relationship between sentence-level comprehension and passage comprehension.


1972 ◽  
Vol 15 (4) ◽  
pp. 852-860 ◽  
Author(s):  
Zoe Zehel ◽  
Ralph L. Shelton ◽  
William B. Arndt ◽  
Virginia Wright ◽  
Mary Elbert

Fourteen children who misarticulated some phones of the /s/ phoneme were tape recorded articulating several lists of items involving /s/. The lists included the Mc-Donald Deep Test for /s/, three lists similar to McDonald’s but altered in broad context, and an /s/ sound production task. Scores from lists were correlated, compared for differences in means, or both. Item sets determined by immediate context were also compared for differences between means. All lists were found to be significantly correlated. The comparison of means indicated that both broad and immediate context were related to test result. The estimated “omega square” statistic was used to evaluate the percentage of test score variance attributable to context.


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