Biomedical subjects

Dimiter M Dimitrov

Publications and source records attributed to Dimiter M Dimitrov.

6 recordsLinked to original sources

PubMed2007

Effects of a teen pregnancy prevention program on teens' attitudes toward sexuality: A latent trait modeling approach.

The purpose of this study was to examine the effects of program interventions in a school-based teen pregnancy program on hypothesized constructs underlying teens' attitudes toward sexuality. An important task related to this purpose was the validation of the constructs and their stability from pre- to postintervention measures. Data from 1,136 middle grade students were obtained from an earlier evaluation of an abstinence-based teen pregnancy prevention program (S. Weed, I. Ericksen, G. Grant, & A. Lewis, 2002). Latent trait structural equation modeling was used to evaluate the impact of the intervention program on changes in constructs of teens' attitudes toward sexuality. Gender was also taken into consideration. This investigation provides credible evidence that both 1st- and 2nd-order constructs related to measures of teens' attitudes toward risky sexual behavior are sufficiently stable and sensitive to detect program effects.

Adolescent↗

PubMed2006

Adjusted Rasch person-fit statistics.

Two frequently used parametric statistics of person-fit with the dichotomous Rasch model (RM) are adjusted and compared to each other and to their original counterparts in terms of power to detect aberrant response patterns in short tests (10, 20, and 30 items). Specifically, the cube root transformation of the mean square for the unweighted person-fit statistic, t, and the standardized likelihood-based person-fit statistic Z3 were adjusted by estimating the probability for correct item response through the use of symmetric functions in the dichotomous Rasch model. The results for simulated unidimensional Rasch data indicate that t and Z3 are consistently, yet not greatly, outperformed by their adjusted counterparts, denoted t* and Z3*, respectively. The four parametric statistics, t, Z3, t*, and Z3*, were also compared to a non-parametric statistic, HT, identified in recent research as outperforming numerous parametric and non-parametric person-fit statistics. The results show that HT substantially outperforms t, Z3, t*, and Z3* in detecting aberrant response patterns for 20-item and 30-item tests, but not for very short tests of 10 items. The detection power of t, Z3, t*, and Z3*, and HT at two specific levels of Type I error, .10 and .05 (i.e., up to 10% and 5% false alarm rate, respectively), is also reported.

Humans↗

PubMed2006

Comparing groups on latent variables: a structural equation modeling approach.

Structural equation modeling (SEM) provides a dependable framework for testing differences among groups on latent variables (constructs, factors). The purpose of this article is to illustrate SEM-based testing for group mean differences on latent variables. Related procedures of confirmatory factor analysis and testing for measurement invariance across compared groups are also presented in the context of rehabilitation research.

Analysis of Variance↗

PubMed2003

Psychometric analysis of performance on categories of client needs and nursing process with the NLN Diagnostic Readiness Test.

This article provides psychometric analysis of the performance of nursing students on categories of client needs (CN) and nursing process (NP) measured by the NLN Diagnostic Readiness Test (NLN-DRT) for RN licensure. While analyses of items and number-right score performance with NLN tests are well documented, the analysis of proficiency on categories that organize items at the conceptual level is limited to reporting basic classical statistics (e.g., proportion of correct scores and percentiles). The psychometric analysis of proficiency on categories of CN and NP in this article is based on item response theory and takes into account that the binary scores on these 2 categories (1 = mastered, 0 = nonmastered) are obtained through summative standardized scoring and not through direct responses of examinees. NLN-DRT data for a local population of 646 students enrolled in an NLN accredited associate degree program was obtained 3 weeks prior to graduation. This article illustrates the application of IRT using the Rasch Model and the 2-parameter logistic model in a method of psychometric analysis that deals with proficiency on conceptual categories and provides measurement feedback to nursing educators for curriculum (or instruction) intervention in a specific educational context. Among the components of such feedback provided in this article are: (a) difficulty, discrimination, and characteristic curves of CN and NP categories, (b) performance patterns by level of success on each category, and (c) domain scores by ability levels for the population of nursing students. The Rasch Model, which was calculated using RASCAL, did not fit the data with the categories of CN or NP at the .05 level of statistical significance. However, the 2-parameter logistic model fit the data with both CN and NP categories while using the XCALIBRE computer program. The IRT approach used in this article demonstrated some measurement perspectives on linking an instrument's conceptual base to theory in the context of nursing education, and provide valuable measurement feedback for improving the quality of curriculum and teaching in institutions that use the NLN-DRT in their assessment practice.

Education, Nursing, Associate↗

PubMed2003

Pretest-posttest designs and measurement of change.

The article examines issues involved in comparing groups and measuring change with pretest and posttest data. Different pretest-posttest designs are presented in a manner that can help rehabilitation professionals to better understand and determine effects resulting from selected interventions. The reliability of gain scores in pretest-posttest measurement is also discussed in the context of rehabilitation research and practice.

Analysis of Variance↗

PubMed2003

Reliability and true-score measures of binary items as a function of their Rasch difficulty parameter.

This article provides formulas for expected true-score measures and reliability of binary items as a function of their Rasch difficulty when the trait (ability) distribution is normal or logistic. The proposed formulas have theoretical value and can be useful in test development, score analysis, and simulation studies. Once the items are calibrated with the dichotomous Rasch model, one can estimate (without further data collection) the expected values for true-score measures (e.g., domain score, true score variance, and error variance for the number-right score) and reliability for both norm-referenced and criterion-referenced interpretations. Thus, given a bank of Rasch calibrated items, one can develop a test with desirable values of population true-score measures and reliability or compare such measures for subsets of items that are grouped by substantive characteristics (e.g., content areas or strands of learning outcomes). An illustrative example for using the proposed formulas is also provided.

Humans↗