Thesis (doctoral)--Katholieke Universiteit te Nijmegen, 1979. / Summary in Dutch. Includes bibliographical references (p. 217-223).

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Thesis (doctoral)--Katholieke Universiteit te Nijmegen, 1983. / "Stellingen" ([2] p.) inserted. Summary in Dutch. Includes bibliographical references (p. 255-270).

Rating scales involving more than two response categories are a popular response format in measurement in education, health and business sciences. Their primary purpose lies in the increase of information and thus measurement precision. For these objectives to be met, the response scale has to provide valid scores with higher numbers reflecting more of the property to be measured. Thus, the response scale is closely linked to construct validity since any kind of malfunctioning would jeopardize measurement. While tests of fit are not necessarily sensitive to violations of the assumed order of response categories, the order of empirical threshold estimates provides insight into the functionality of the scale. The Rasch model and, specifically, the so-called Rasch-Andrich thresholds are unique in providing this kind of evidence. The conclusion whether thresholds are to be considered truly ordered or disordered can be based on empirical point estimates of thresholds. Alternatively, statistical tests can be carried out taking standard errors of threshold estimates into account. Such tests might either stress the need for evidence of ordered thresholds or the need for a lack of evidence of disordered thresholds. Both approaches are associated with unacceptably high error rates, though. A hybrid approach that accounts for both evidence of ordered and disordered thresholds is suggested as a compromise. While the usefulness of statistical tests for a given data set is still limited, they provide some guidance in terms of a modified response scale in future applications.

Satisfaction is a central concept in marketing. However in recent years, satisfaction has come under increasing criticism. Its ability to predict post-purchase behaviour has not been established and the importance of the word satisfaction to consumers has been questioned. Current satisfaction measures are inadequate, as they fail to discriminate between respondents, with the majority of respondents regularly endorsing the most positive answer category available. The limited discrimination of existing scales suggests that only a small part of the unfavourable/favourable evaluation, rather than the entire dimension is being measured. The overwhelming use of the most positive answer category, in traditional scales, illustrates that they fail to capture highly positive evaluations. Affective Response to Consumption (ARC) is conceptualised as an extension to satisfaction. The conceptualisation shifts the emphasis from a scale relying on one, rather weak, emotional feeling -- satisfaction -- to a multitude of emotional feelings, including highly positive terms. A scale measuring ARC is developed in an alternative measurement paradigm -- Rasch Modelling -- to the dominant paradigm for scale development in marketing -- Classical Test Theory. The characteristics of Rasch Modelling are particularly useful, when measuring a concept like ARC, that captures the entire dimension of unfavourable/favourable evaluations and includes terms of markedly different intensity.

This study is aim to develop and validate the Creative Life Style Check List by analysis of the literature scale and integration expert opinions. This scale for the self-report scale, a total of 28 questions, uses Likert five-point scale scoring. There were four subscale, ¡§wildly life experiences ¡§, ¡§imagination¡¨, ¡§new creation and expression¡¨, and ¡§openness mind¡¨. Purposive sampling method to extract the Sun Yat-sen University, Ministry of students as the study sample, the pre-pilot scale a total of 304 samples, a total of 983 formal scale samples. The MPCM analysis by the Rasch model is to examine the scale of reliability and validity. Content validity Infit MNSQ is between 0.75 ~ 1.3logits, each subscale internal consistency from .831 to .893. Scale internal consistency reliability was .93. Construct validity of the comparison of PCM and MPCM that estimated residuals of MPCM smaller than PCM. That means four-dimensions model more fit than one-dimension model. The correlation between each subscale is in the range of 0.684 ~ 0.861. The validity generalization, the scale of the boys and girls difficulty estimate differences in the range of 0.000 to 0.198, on behalf of this scale is no gender differential item functioning (DIF). Participants separated reliability coefficient of 0.844 to 0.900 that means this scale can stability measure the location of participants of the creativity construct. Difficulty estimated values of each subscale in the formal questionnaire and the pre-test scale ranged from .815 to .944 is high correlation. And p <0.05 show the scale has cross-sample stability.

Item response theory models (IRT) are increasingly becoming established in social science research, particularly in the analysis of performance or attitudinal data in psychology, education, medicine, marketing and other fields where testing is relevant. We propose the R package eRm (extended Rasch modeling) for computing Rasch models and several extensions. A main characteristic of some IRT models, the Rasch model being the most prominent, concerns the separation of two kinds of parameters, one that describes qualities of the subject under investigation, and the other relates to qualities of the situation under which the response of a subject is observed. Using conditional maximum likelihood (CML) estimation both types of parameters may be estimated independently from each other. IRT models are well suited to cope with dichotomous and polytomous responses, where the response categories may be unordered as well as ordered. The incorporation of linear structures allows for modeling the effects of covariates and enables the analysis of repeated categorical measurements. The eRm package fits the following models: the Rasch model, the rating scale model (RSM), and the partial credit model (PCM) as well as linear reparameterizations through covariate structures like the linear logistic test model (LLTM), the linear rating scale model (LRSM), and the linear partial credit model (LPCM). We use an unitary, efficient CML approach to estimate the item parameters and their standard errors. Graphical and numeric tools for assessing goodness-of-fit are provided. (authors' abstract)

Item response theory models (IRT) are increasingly becoming established in social science research, particularly in the analysis of performance or attitudinal data in psychology, education, medicine, marketing and other fields where testing is relevant. We propose the R package eRm (extended Rasch modeling) for computing Rasch models and several extensions. A main characteristic of some IRT models, the Rasch model being the most prominent, concerns the separation of two kinds of parameters, one that describes qualities of the subject under investigation, and the other relates to qualities of the situation under which the response of a subject is observed. Using conditional maximum likelihood (CML) estimation both types of parameters may be estimated independently from each other. IRT models are well suited to cope with dichotomous and polytomous responses, where the response categories may be unordered as well as ordered. The incorporation of linear structures allows for modeling the effects of covariates and enables the analysis of repeated categorical measurements. The eRm package fits the following models: the Rasch model, the rating scale model (RSM), and the partial credit model (PCM) as well as linear reparameterizations through covariate structures like the linear logistic test model (LLTM), the linear rating scale model (LRSM), and the linear partial credit model (LPCM). We use an unitary, efficient CML approach to estimate the item parameters and their standard errors. Graphical and numeric tools for assessing goodness-of-fit are provided. (author's abstract) / Series: Research Report Series / Department of Statistics and Mathematics

Measures of psychological attributes abound in the social sciences as much as measures of physical properties do in the physical sciences. However, there are crucial differences between the scientific underpinning of measurement. While measurement in the physical sciences is supported by empirical evidence that demonstrates the quantitative nature of the property assessed, measurement in the social sciences is, in large part, made possible only by a vague, discretionary definition of measurement that places hardly any restrictions on empirical data. Traditional psychometric analyses fail to address the requirements of measurement as defined more rigorously in the physical sciences. The construct definitions do not allow for testable predictions; and content validity becomes a matter of highly subjective judgment. In order to improve measurement of psychological attributes, it is suggested to, first, readopt the definition of measurement in the physical sciences; second, to devise an elaborate theory of the construct to be measured that includes the hypothesis of a quantitative attribute; and third, to test the data for the structure implied by the hypothesis of quantity as well as predictions derived from the theory of the construct. (author's abstract)

Thesis advisor: Pamela J. Grace / Background: As established in professional codes of ethics, critical care nurses must be equipped to provide good (ethical) patient care. This requires ethical awareness, which involves recognizing the ethical implications of all nursing actions (ranging from the mundane to the dilemmatic). Ethical awareness is imperative in successfully addressing patient needs, however, evidence suggests that the ethical import of everyday issues may often go unnoticed by nurses in practice. Assessing nurses’ ethical awareness is a necessary first step in preparing nurses to identify and manage ethical issues in the highly dynamic critical care environment. Purpose: To use Rasch principles to develop a psychometrically sound instrument to assess the nature and extent of critical care nurses’ ethical awareness in the context of everyday nursing practice, and to assess the success of scale development using a Rasch model. Method: An item bank representing nursing actions was developed (33 items). Content validity testing with nursing ethics experts (n = 5) was performed (CVI-I = 1). Eighteen items were selected for face validity testing with graduate nursing students (n = 7). After revisions, two full-scale pilot administrations were performed to run item analyses. Sample: Critical care nurses (n = 116) at a large academic teaching hospital in New England. Results: Pilot test analyses suggest sufficient item invariance across samples and sufficient construct validity. Final analyses demonstrate a progression of items uniformly along a hierarchical continuum; items that match respondent ability levels; response categories that are sufficiently used; a Principle Components Analysis demonstrating randomness of residuals, and adequate internal consistency (Cronbach’s α = 0.83). Mean ethical awareness scores were in the low/moderate range (M = 34.9/54; logit = -0.21). Conclusion: The results of this study suggest the Ethical Awareness Scale (EAS) is a psychometrically sound, reliable, and valid measure of ethical awareness in critical care nurses. / Thesis (PhD) — Boston College, 2017. / Submitted to: Boston College. Connell School of Nursing. / Discipline: Nursing.