Charles E Werts
Biographic Data
| ID | 257972 |
|---|---|
| NAME | Charles E Werts |
| GIVEN NAMES | Charles E |
| FAMILY NAME | Werts |
| SIGNATURE | WERTS C E |
| AFFILIATIONS | Educational Testing Service |
| VERIFIED | No |
| TOTAL WORKS | 48 |
| TOTAL CITATIONS | 81 |
| AUTHOR COUNT | 48 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1965 |
| LATEST PUBLICATION YEAR | 1981 |
| H-INDEX | 5 |
Applications of Quasi-Markov Simplex Models Across Populations
A linear structural model for comparing quasi-Markov models across populations is demonstrated. A confirmatory factor analysis formulation of the simplex model is also developed for between group comparisons. A variety of possible applications of this approach are suggested
Using Longitudinal Data to Estimate Reliability in the Presence of Correlated Measurement Errors
Test-retest correlations can lead to biased reliability estimates when there is instability of the true scores in the interval between tests and/or when the measurement errors are correlated. Using three occasion data on the Test of Standard Written English and essay ratings, an analysis is demonstrated which separates true score instability and correlated errors
A Confirmatory Approach To Calibration Congeneric Measures
This paper demonstrates how the problem of calibrating measures can be formulated in terms of confirmatory factor analysis. The relationships between traditional approaches (Angoff, 1971) and a confirmatory factor approach are specified
Estimation and Testing of Partial Covariances, Correlations, and Regression Weights Using Maximum Likelihood Factor Analysis
It is shown how partial covariance, part and partial correlation, and regression weights can be estimated and tested for significance by means of a factor analytic model. Comparable partial covariance, correlations, and regression weights have identical significance tests
Confirmatory Factor Analysis Applications
Procedures for simultaneous confirmatory factor analysis in several populations are useful in a wide variety of problems. This is demonstrated with examples involving missing data, comparison of part correlations between groups, testing the equality of regression weights between groups with multiple indicators of each variable, and the formulation of growth models. Corrections for attenuation can be incorporated into analysis of covariance and an…
Reliability of College Grades From Longitudinal Data
Jöreskog's (1970a) procedure for the analysis of simplex models was used to test Humphreys' (1968) assertion that eight semesters of undergraduate grade-point averages have a simplex form. Not only was this assertion confirmed but precise estimates of reliability and of unattenuated correlations were obtained
A General Method of Estimating the Reliability of a Composite
A procedure for estimating the reliability of a factorially complex composite is considered
The Use Of Analysis Of Covariance Structures For Comparing The Psychometric Properties Of Multiple Variables Across Populations
It is common practice to assume that the dependent variables in differential prediction studies, and analysis of variance and co-variance designs are characterized by certain psychometric properties which are invariant across the subgroups of interest. More specifically, the accuracy of the results of such analyses depends on the assumption that the dependent variables are measuring the constructs in the same metrics with equivalent reliabilities…
Validating Psychometric Assumptions within and between Several Populations
The psychometric application of Jöreskog's (Note 1) procedure for simultaneous factor analysis in several populations is illustrated. Using Scholastic Aptitude Test data from two samples, procedures are shown for checking test construction assumptions about units of measurement and error variance, within and between samples
A Simplex Model for Analyzing Academic Growth
A simplex model is presented for the analysis of longitudinal academic growth variables in which only one measure is obtained at each time. When this model fits the observed data, then reliabilities and unattenuated correlations can be estimated except for the first and last periods
A Maximum Likelihood Solution To The Errors In Variables And Errors In Equations Model
This article provides a maximum likelihood estimation procedure for a linear model with errors in variables. Warren, et al, provide a least squares procedure for the same problem but which may be shown to be a special case of the more general approach suggested here. Also unlike the least squares approach, this formulation permits tests of the independence of measurement errors as well as the equality of measurement units. The importance of testi…
Analysis implications of the choice of a structural model in the nonequivalent control group design
Analysis implications of the choice of a structural model in the nonequivalent control group design
Intellectual Status and Intellectual Growth, Again
The simplex model is used to correct for attenuation in the correlation of status with gain for a variety of academic skills. Implications of the results for the study of the determinants of academic growth are discussed and also some possible implications for classroom instruction
Analyzing Ratings With Correlated Intrajudge Measurement Errors
A procedure is presented for the analysis of rating data with correlated intrajudge and uncorrelated interjudge measurement errors. Correlations between true scores on different rating dimensions, reliabilities for each judge on each dimension and correlations between intrajudge errors can be estimated given a minimum of three raters and two dimensions
Structural Equations As An Aid In The Interpretation Of The Non-Orthogonal Analysis Of Variance
Various computational methods for non-orthogonal analysis of variance designs lead to tests of different hypotheses. The purpose of this paper is to define the structural equations underlying these hypotheses and thus to indicate under what conditions one or more methods may be preferable
Comparison of correlations, variances, covariances, and regression weights with or without measurement error
Intraclass Reliability Estimates
Intraclass correlation reliablity estimates are based on the assumption that the various measures are equivalent. Jöreskog's (1970) general model for the analysis of covariance structures can be used to test the validity of this assumption
Errors of Inference Due to Errors of Measurement
Another Perspective on "Linear Regression, Structural Relations, and Measurement Error"
A Congeneric Model for Platonic True Scores
To resolve recent controversy between Klein and Cleary and Levy, a model for dichotomous congeneric items is presented which has mean errors of zero, dichotomous true scores that are uncorrelated with errors, and errors that are mutually uncorrelated
Identification and Estimation in Path Analysis with Unmeasured Variables
The application of Joreskog's (1970a) general model for the analysis of covariance structures to several path models involving unmeasured variables is discussed. When these path models have a factor-analytic structure, a simple heuristic rule derived from factor analysis may be helpful in determining the identification status of parameters
A Multitrait-Multimethod Model for Studying Growth
EDRS Price MF-$0.65 HC-$3.29 Analysis of Covariance, Analysis of Variance, Correlation, *Factor Analysis, *Factor Structure, Hypothesis Testing, *Mathematical Models, *Mathematics, *Personal Growth, Statistics The logical structure of the Campbell and Fiske multitrait-multimethod approach is applied to the problem of studying growth and its determinants. The resulting model is a special case of Joreskog's general model for the analysis of covaria…
Estimating True Scores Using Group Membership
Considerations when Making Inferences within the Analysis of Covariance Model
"Comment on "The Estimation of Measurement Error in Panel Data
Path analysis
Assumptions in making causal inferences from part correlations, partal correlations, and partial regression coefficients
A general linear model for studying growth
Identification and Estimation in Path Analysis with Unmeasured Variables
The application of Joreskog's (1970a) general model for the analysis of covariance structures to several path models involving unmeasured variables is discussed. When these path models have a factor-analytic structure, a simple heuristic rule derived from factor analysis may be helpful in determining the identification status of parameters
Cautions in Applying Various Procedures for Determining the Reliability and Validity of Multiple-Item Scales
Analyzing School Effects
In the usual school effects studies three types of variables can be distinguished: (a) school measures (i.e., characteristics of the school such as financial resources and characteristics of the instructional program); (b) input variables (i.e., the student characteristics at the time he enters the system); and (c) output variables (i.e., student characteristics after being in the system for a given period of time). In these studies the school ef…
Path Analysis
The technique of path analysis, recently introduced into the sociological literature by Duncan, can by a powerful aid in clarifying complex causal arguments. To demonstrate this pont, a study by Davis of the effect of college "selectivity" on career aspirations was reconsidered from the standpoint of a path analytic model
Intellectual Status and Intellectual Growth, Again
The simplex model is used to correct for attenuation in the correlation of status with gain for a variety of academic skills. Implications of the results for the study of the determinants of academic growth are discussed and also some possible implications for classroom instruction
Comparison of correlations, variances, covariances, and regression weights with or without measurement error
The Partitioning of Variance in School Effects Studies
One of the most common procedures in school effects studies is multivariate regression analysis employed in conjunction with an input-output model. In the usual, two-step regression method, student input is controlled by first computing from the input variables an expected output for each school. The difference between the observed and the expected output is then used as the dependent variable, and the school environment variables as the independ…
Career Changes in College
Changes in career plans during the freshman year were studied using a sample of male students from 248 heterogeneous colleges who were planning careers as engineers (N= 1999), teachers (N= 1816), physicians (N=1576), businessmen (N=928), lawyers (N=869), chemists N(= 484), accountants (N=420), and physicists (N=391). The results support the generalization that in terms of academic ability and social class background, students who are unlike the m…
"Comments on Boyle's "Path Analysis and Ordinal Data
Analyzing College Effects
A commonly used procedure in studying college effects involves an input-output model in which student input is controlled by using regression analysis to compute an expected output (e.g., Astin, 1963, 1964; Thistlethwaite & Wheeler, 1966). The correlation of a school environment variable with the residual output (i.e. actual minus expected output) is interpreted as a measure of the school's influence on the output. Although sometimes labeled a pa…
Determinants of Changes in Career Plans During College
According to Davis's theory of the determinants of career changes during college, deviants in a given field tend to switch out, and students with traits characteristic of the field tend to switch in. Thus it is predicted that each career field should gradually become more homogeneous, and that the differences between fields should increase during the college years. Reanalysis of data from a recent study by Werts indicate that these predictions ar…
Factors Related to Behavior in Labor
modified. Fortunately, we have both the experienced personnel and the technological capacity to construct a Manpower System, exercise it, and train personnel by it. We do not have to accept partial fulfillment from the testing of one or another minuscule model when complete fulfillment from the testing of the entire Manpower System is available. We therefore propose that these two models of Illness and Health be accepted as a basis for the logica…
Social Class and Initial Career Choice of College Freshmen
Davis' study of social class effects on career preferences usicxg a composite neasure of SES level (including type of father's occupation, father's education and income) indicates definite patterns in career preferences by different SES groups. The present study reconfirms Davis' findings concerning these general SES effects, such as the overchoice of medicine and law by higher SES groups. However, by obtaining the father's specific occupation (e…
Career Changes in College
Changes in career plans during the freshman year were studied using a sample of male students from 248 heterogeneous colleges who were planning careers as engineers (N= 1999), teachers (N= 1816), physicians (N=1576), businessmen (N=928), lawyers (N=869), chemists N(= 484), accountants (N=420), and physicists (N=391). The results support the generalization that in terms of academic ability and social class background, students who are unlike the m…
Career Choice Patterns
Data on 76,015 male and 51,110 female college freshmen at 248 colleges and universities were analyzed to determine how father's education and high school grades were related to career choice. It was found that students at each high school grade average level tend to have different career choices depending on their father's education. A separate study of career choices of women indicated that those who choose nontraditional careers (traditional ca…
The Partitioning of Variance in School Effects Studies
One of the most common procedures in school effects studies is multivariate regression analysis employed in conjunction with an input-output model. In the usual, two-step regression method, student input is controlled by first computing from the input variables an expected output for each school. The difference between the observed and the expected output is then used as the dependent variable, and the school environment variables as the independ…
Analyzing College Effects
A commonly used procedure in studying college effects involves an input-output model in which student input is controlled by using regression analysis to compute an expected output (e.g., Astin, 1963, 1964; Thistlethwaite & Wheeler, 1966). The correlation of a school environment variable with the residual output (i.e. actual minus expected output) is interpreted as a measure of the school's influence on the output. Although sometimes labeled a pa…
Determinants of Changes in Career Plans During College
According to Davis's theory of the determinants of career changes during college, deviants in a given field tend to switch out, and students with traits characteristic of the field tend to switch in. Thus it is predicted that each career field should gradually become more homogeneous, and that the differences between fields should increase during the college years. Reanalysis of data from a recent study by Werts indicate that these predictions ar…
A Comparison of Male vs. Female College Attendance Probabilities
The ratio of males to females in a sample of 127,125 college freshmen was computed for various fathers' occupations, levels of fathers' education, and academic achievement. Among low achievers, boys were much more likely than girls to enter college, while among high achievers, boys and girls were equally likely to enter college. Among low-SES students, boys were much more likely than girls to go to college. Boys and girls whose fathers were close…
Path Analysis
The technique of path analysis, recently introduced into the sociological literature by Duncan, can by a powerful aid in clarifying complex causal arguments. To demonstrate this pont, a study by Davis of the effect of college "selectivity" on career aspirations was reconsidered from the standpoint of a path analytic model
Lord's paradox
Analyzing School Effects
In the usual school effects studies three types of variables can be distinguished: (a) school measures (i.e., characteristics of the school such as financial resources and characteristics of the instructional program); (b) input variables (i.e., the student characteristics at the time he enters the system); and (c) output variables (i.e., student characteristics after being in the system for a given period of time). In these studies the school ef…
Assumptions in making causal inferences from part correlations, partal correlations, and partial regression coefficients
The Partitioning of Variance in School Effects Studies
Cautions in Applying Various Procedures for Determining the Reliability and Validity of Multiple-Item Scales
Path analysis
A general linear model for studying growth
The Relationship of Parental Education to Achievement Test Performance of Girls vs. Boys
High scorers on the National Merit Scholarship Qualifying Test were crosscategorized by levels of father's and mother's education. The relative probability of high achievement for males as compared with females of the same background is then indicated by the ratio of the number of males to the number of females in each category. This ratio was found to decrease with increasing father's and mother's education; however, the association of father's …
Considerations when Making Inferences within the Analysis of Covariance Model
Problems with Inferring Treatment Effects from Repeated Measures
The Interpretation of Regression Coefficients in a School Effects Model
Analyzing School Effects
THE analysis of variance, covariance method (ANCOVA) has been employed in nonexperimental school effects studies to control for differential input when studying the differential impact of schools as a categorical treatment factor on some output variable. One of the numerous hazards (Smith, 1957) to interpreting these ANCOVA findings results from the use of input measures known to have considerable errors of measurement. As a consequence, in-put m…
Casual assumptions in various procedures for the least squares analysis of categorical data
"Comments on Boyle's "Path Analysis and Ordinal Data
"Comment on "The Estimation of Measurement Error in Panel Data
A Multitrait-Multimethod Model for Studying Growth
EDRS Price MF-$0.65 HC-$3.29 Analysis of Covariance, Analysis of Variance, Correlation, *Factor Analysis, *Factor Structure, Hypothesis Testing, *Mathematical Models, *Mathematics, *Personal Growth, Statistics The logical structure of the Campbell and Fiske multitrait-multimethod approach is applied to the problem of studying growth and its determinants. The resulting model is a special case of Joreskog's general model for the analysis of covaria…
Mathematics (42 works) · Psychology (40 works) · Statistics (39 works) · Econometrics (36 works) · Computer Science (22 works) · Advanced Statistical Methods and Models (13 works) · Psychometric Methodologies and Testing (12 works) · School Choice and Performance (10 works) · Mathematics education (9 works) · Regression (9 works)