| 1. |
- Brenner, Sten-Olof, et al.
(författare)
-
The stress chain : A longitudinal confirmatory study of teacher stress, coping and social support
- 1985
-
Ingår i: Journal of Occupational Psychology. - : Wiley. - 0305-8107. ; 58:1, s. 1-13
-
Tidskriftsartikel (refereegranskat)abstract
- Tested a conceptual core model of the teacher stress process, which was assumed to be invariant, on longitudinal data obtained from 63 teachers. LISREL analysis confirmed the goodness of fit of the model. Ss' relations to and perceptions of pupils as a stress source resulted in general strain and in turn led to various stress reactions. Ss who perceived students as stressors at the middle of the 1st term reported general strain and impaired somatic and mental health at the end of the school year. It is concluded that the major part of successful coping seems to take place during the 1st half of the school year; later, only minor changes are noticed. The short-term perspective on coping should guide further studies on teacher stress. (30 ref
|
|
| 2. |
- Bränberg, Kenny, 1956-
(författare)
-
Observed score equating with covariates
- 2010
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In test score equating the focus is on the problem of finding the relationship between the scales of different test forms. This can be done only if data are collected in such a way that the effect of differences in ability between groups taking different test forms can be separated from the effect of differences in test form difficulty. In standard equating procedures this problem has been solved by using common examinees or common items. With common examinees, as in the equivalent groups design, the single group design, and the counterbalanced design, the examinees taking the test forms are either exactly the same, i.e., each examinee takes both test forms, or random samples from the same population. Common items (anchor items) are usually used when the samples taking the different test forms are assumed to come from different populations. The thesis consists of four papers and the main theme in three of these papers is the use of covariates, i.e., background variables correlated with the test scores, in observed score equating. We show how covariates can be used to adjust for systematic differences between samples in a non-equivalent groups design when there are no anchor items. We also show how covariates can be used to decrease the equating error in an equivalent groups design or in a non-equivalent groups design. The first paper, Paper I, is the only paper where the focus is on something else than the incorporation of covariates in equating. The paper is an introduction to test score equating, and the author's thoughts on the foundation of test score equating. There are a number of different definitions of test score equating in the literature. Some of these definitions are presented and the similarities and differences between them are discussed. An attempt is also made to clarify the connection between the definitions and the most commonly used equating functions. In Paper II a model is proposed for observed score linear equating with background variables. The idea presented in the paper is to adjust for systematic differences in ability between groups in a non-equivalent groups design by using information from background variables correlated with the observed test scores. It is assumed that conditional on the background variables the two samples can be seen as random samples from the same population. The background variables are used to explain the systematic differences in ability between the populations. The proposed model consists of a linear regression model connecting the observed scores with the background variables and a linear equating function connecting observed scores on one test forms to observed scores on the other test form. Maximum likelihood estimators of the model parameters are derived, using an assumption of normally distributed test scores, and data from two administrations of the Swedish Scholastic Assessment Test are used to illustrate the use of the model. In Paper III we use the model presented in Paper II with two different data collection designs: the non-equivalent groups design (with and without anchor items) and the equivalent groups design. Simulated data are used to examine the effect - in terms of bias, variance and mean squared error - on the estimators, of including covariates. With the equivalent groups design the results show that using covariates can increase the accuracy of the equating. With the non-equivalent groups design the results show that using an anchor test together with covariates is the most efficient way of reducing the mean squared error of the estimators. Furthermore, with no anchor test, the background variables can be used to adjust for the systematic differences between the populations and produce unbiased estimators of the equating relationship, provided that the “right” variables are used, i.e., the variables explaining those differences. In Paper IV we explore the idea of using covariates as a substitute for an anchor test with a non-equivalent groups design in the framework of Kernel Equating. Kernel Equating can be seen as a method including five different steps: presmoothing, estimation of score probabilities, continuization, equating, and calculating the standard error of equating. For each of these steps we give the theoretical results when observations on covariates are used as a substitute for scores on an anchor test. It is shown that we can use the method developed for Post-Stratification Equating in the non-equivalent groups with anchor test design, but with observations on the covariates instead of scores on an anchor test. The method is illustrated using data from the Swedish Scholastic Assessment Test.
|
|
| 3. |
|
|
| 4. |
- Kraus, Katrin, 1979-
(författare)
-
On the Measurement of Model Fit for Sparse Categorical Data
- 2012
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis consists of four papers that deal with several aspects of the measurement of model fit for categorical data. In all papers, special attention is paid to situations with sparse data.The first paper concerns the computational burden of calculating Pearson's goodness-of-fit statistic for situations where many response patterns have observed frequencies that equal zero. A simple solution is presented that allows for the computation of the total value of Pearson's goodness-of-fit statistic when the expected frequencies of response patterns with observed frequencies of zero are unknown.In the second paper, a new fit statistic is presented that is a modification of Pearson's statistic but that is not adversely affected by response patterns with very small expected frequencies. It is shown that the new statistic is asymptotically equivalent to Pearson's goodness-of-fit statistic and hence, asymptotically chi-square distributed.In the third paper, comprehensive simulation studies are conducted that compare seven asymptotically equivalent fit statistics, including the new statistic. Situations that are considered concern both multinomial sampling and factor analysis. Tests for the goodness-of-fit are conducted by means of the asymptotic and the bootstrap approach both under the null hypothesis and when there is a certain degree of misfit in the data. Results indicate that recommendations on the use of a fit statistic can be dependent on the investigated situation and on the purpose of the model test. Power varies substantially between the fit statistics and the cause of the misfit of the model. Findings indicate further that the new statistic proposed in this thesis shows rather stable results and compared to the other fit statistics, no disadvantageous characteristics of the fit statistic are found.Finally, in the fourth paper, the potential necessity of determining the goodness-of-fit by two sided model testing is adverted. A simulation study is conducted that investigates differences between the one sided and the two sided approach of model testing. Situations are identified for which two sided model testing has advantages over the one sided approach.
|
|
| 5. |
|
|
| 6. |
|
|
| 7. |
- Wänström, Linda, 1972-
(författare)
-
Intelligence and models for cognitive development
- 2007
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This dissertation focuses on cognitive development. In papers I and II, I study a special model, the second order latent growth curve model, that can be used to study cognitive development. Algebraic expressions for the variance of the estimation of slope differences are given. They may be used to calculate the sample sizes needed to detect slope differences between groups. Illustrations of the formulas indicate that sample sizes decrease with effect size, number of indicators and their reliabilities, frequency of observation and duration of the study. In addition, observations near the beginning and end are more important than observations in the middle, and needed sample sizes increase with attrition. Smaller sample sizes are also needed in studies in which baseline levels between groups may be assumed equal, and correlations between factors can either increase or decrease needed sample size.Papers III and IV address different aspects of cognitive development. The Flynn effect refers to the observed fact that IQ scores increase over time. In Paper III, we suggest outlining the boundaries within which this effect occurs prior to investigating possible causes. We observe an effect in a test in a large American dataset. This dataset contains information that can be used to outline these boundaries as well as to search for possible causes. Paper IV addresses the observed correlation between sibship size or birth order and cognitive ability. If sibship size negatively affects cognitive ability in children, this should be detected studying children’s cognitive development prior to, and after, the birth of a sibling. Using longitudinal multilevel analyses on a large sample of American children from ages five to fourteen, differences between children of different sibship sizes are noted. Their cognitive abilities do not change following the birth of a sibling however.
|
|
| 8. |
|
|
