Browse
Submit Data
Databases
API
Help

Dataset Information

18 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Modeling Asymmetry in the Time-Distance Relation of Ordinal Personality Items.

ABSTRACT: In analyzing responses and response times to personality questionnaire items, models have been proposed which include the so-called "inverted-U effect." These models predict that response times to personality test items decrease as the latent trait value of a given person gets closer to the attractiveness of an item. Initial studies into these models have focused on dichotomous personality items, and more recently, models for Likert-type scale items have been proposed. In all these models, it is assumed that the inverted-U effect is symmetrical around 0, while, as will be explained in this article, there are substantive and statistical reasons to study this assumption. Therefore, in this article, a general inverted-U model is proposed which accommodates two sources of asymmetry between the response times and the attractiveness of the items. The viability of this model is demonstrated in a simulation study, and the model is applied to the responses and response times of the Temperament and Character Inventory-Revised, covering a broad range of personality dimensions.

SUBMITTER: Molenaar D

PROVIDER: S-EPMC8042558 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

The Abbreviation of Personality, or how to Measure 200 Personality Scales with 200 Items.

Project description:Personality researchers have recently advocated the use of very short personality inventories in order to minimize administration time. However, few such inventories are currently available. Here I introduce an automated method that can be used to abbreviate virtually any personality inventory with minimal effort. After validating the method against existing measures in Studies 1 and 2, a new 181-item inventory is generated in Study 3 that accurately recaptures scores on 8 different broadband inventories comprising 203 distinct scales. Collectively, the results validate a powerful new way to improve the efficiency of personality measurement in research settings.

| S-EPMC2858332 | biostudies-literature

Modeling continuous response variables using ordinal regression.

Project description:We study the application of a widely used ordinal regression model, the cumulative probability model (CPM), for continuous outcomes. Such models are attractive for the analysis of continuous response variables because they are invariant to any monotonic transformation of the outcome and because they directly model the cumulative distribution function from which summaries such as expectations and quantiles can easily be derived. Such models can also readily handle mixed type distributions. We describe the motivation, estimation, inference, model assumptions, and diagnostics. We demonstrate that CPMs applied to continuous outcomes are semiparametric transformation models. Extensive simulations are performed to investigate the finite sample performance of these models. We find that properly specified CPMs generally have good finite sample performance with moderate sample sizes, but that bias may occur when the sample size is small. Cumulative probability models are fairly robust to minor or moderate link function misspecification in our simulations. For certain purposes, the CPMs are more efficient than other models. We illustrate their application, with model diagnostics, in a study of the treatment of HIV. CD4 cell count and viral load 6 months after the initiation of antiretroviral therapy are modeled using CPMs; both variables typically require transformations, and viral load has a large proportion of measurements below a detection limit.

| S-EPMC5675816 | biostudies-literature

Constructing ordinal partition transition networks from multivariate time series.

Project description:A growing number of algorithms have been proposed to map a scalar time series into ordinal partition transition networks. However, most observable phenomena in the empirical sciences are of a multivariate nature. We construct ordinal partition transition networks for multivariate time series. This approach yields weighted directed networks representing the pattern transition properties of time series in velocity space, which hence provides dynamic insights of the underling system. Furthermore, we propose a measure of entropy to characterize ordinal partition transition dynamics, which is sensitive to capturing the possible local geometric changes of phase space trajectories. We demonstrate the applicability of pattern transition networks to capture phase coherence to non-coherence transitions, and to characterize paths to phase synchronizations. Therefore, we conclude that the ordinal partition transition network approach provides complementary insight to the traditional symbolic analysis of nonlinear multivariate time series.

| S-EPMC5552885 | biostudies-other

Structural change detection in ordinal time series.

Project description:Change-point detection in health care data has recently obtained considerable attention due to the increased availability of complex data in real-time. In many applications, the observed data is an ordinal time series. Two kinds of test statistics are proposed to detect the structural change of cumulative logistic regression model, which is often used in applications for the analysis of ordinal time series. One is the standardized efficient score vector, the other one is the quadratic form of the efficient score vector with a weight function. Under the null hypothesis, we derive the asymptotic distribution of the two test statistics, and prove the consistency under the alternative hypothesis. We also study the consistency of the change-point estimator, and a binary segmentation procedure is suggested for estimating the locations of possible multiple change-points. Simulation results show that the former statistic performs better when the change-point occurs at the centre of the data, but the latter is preferable when the change-point occurs at the beginning or end of the data. Furthermore, the former statistic could find the reason for rejecting the null hypothesis. Finally, we apply the two test statistics to a group of sleep data, the results show that there exists a structural change in the data.

| S-EPMC8367010 | biostudies-literature

Exploring network structure and central items of the Narcissistic Personality Inventory.

Project description:OBJECTIVES:The aim of this work is to explore the Narcissistic Personality Inventory (NPI) using network analysis in a dataset of 942 university students from the French-speaking part of Belgium. METHODS:We estimated an Ising Model for the forty items in the questionnaire and explored item interconnectedness with strength centrality. We provide in the supplementary materials the dataset used for the analyses as well as the full code to ensure the reproducibility of our results. RESULTS:The NPI is presented as an overall positively connected network with items from entitlement, authority and superiority reporting the highest centrality estimates. CONCLUSIONS:Network analysis highlights new properties of items from the NPI. Future studies should endeavor to replicate our findings in other samples, both clinical and non-clinical.

| S-EPMC7051847 | biostudies-literature

Partial least squares path modeling using ordinal categorical indicators.

Project description:This article introduces a new consistent variance-based estimator called ordinal consistent partial least squares (OrdPLSc). OrdPLSc completes the family of variance-based estimators consisting of PLS, PLSc, and OrdPLS and permits to estimate structural equation models of composites and common factors if some or all indicators are measured on an ordinal categorical scale. A Monte Carlo simulation (N [Formula: see text]) with different population models shows that OrdPLSc provides almost unbiased estimates. If all constructs are modeled as common factors, OrdPLSc yields estimates close to those of its covariance-based counterpart, WLSMV, but is less efficient. If some constructs are modeled as composites, OrdPLSc is virtually without competition.

| S-EPMC5794891 | biostudies-literature

Ordinal dose-response modeling approach for the phthalate syndrome.

Project description:BackgroundThe phthalate syndrome (PS) is a collection of related male reproductive developmental effects, ranging in severity, that have been observed in rats after gestational exposure to developmentally-toxic phthalates. For statistical purposes, the PS is defined as a single endpoint and one dose-response analysis is conducted, rather than conducting multiple analyses on each individual endpoint.ObjectiveTo improve dose-response modeling approaches for the PS and other syndromes of effects by accounting for differing severity levels among the endpoints.MethodsOrdinal dose-response modeling was performed on PS data from a published study of diisobutyl phthalate (DIBP) gestational exposure to male Sprague-Dawley rats. To incorporate PS endpoint severity, the endpoints were categorized into ordinal levels based on the expected impact of male developmental endpoint's on fertility. Then, a benchmark dose was estimated for each ordinal level. A bootstrap procedure was used to account for the nested nature of the data, and a sensitivity analysis was performed to assess the bootstrap results. A comparison of the estimates between the ordinal and the dichotomous model was performed.ResultsThe ordinal version of the log-logistic model applied to the data categorized by PS endpoint severity level provided benchmark dose estimates that were closer to each other in value and had lower variability than the traditional dichotomous application. The sensitivity analysis confirmed the validity of the bootstrap results.ConclusionThe ordinal dose-response modeling method accounts for severity differences among dichotomous PS endpoints, can be expanded in the future to include more severity levels, and can be used in both single and cumulative phthalate risk assessments.

| S-EPMC7323710 | biostudies-literature

Ordinal-To-Interval Scale Conversion Tables and National Items for the New Zealand Version of the WHOQOL-BREF.

Project description:The World Health Organisation Quality of Life (WHOQOL) questionnaires are widely used around the world and can claim strong cross-cultural validity due to their development in collaboration with international field centres. To enhance conceptual equivalence of quality of life across cultures, optional national items are often developed for use alongside the core instrument. The present study outlines the development of national items for the New Zealand WHOQOL-BREF. Focus groups with members of the community as well as health experts discussed what constitutes quality of life in their opinion. Based on themes extracted of aspects not contained in the existing WHOQOL instrument, 46 candidate items were generated and subsequently rated for their importance by a random sample of 585 individuals from the general population. Applying importance criteria reduced these items to 24, which were then sent to another large random sample (n = 808) to be rated alongside the existing WHOQOL-BREF. A final set of five items met the criteria for national items. Confirmatory factor analysis identified four national items as belonging to the psychological domain of quality of life, and one item to the social domain. Rasch analysis validated these results and generated ordinal-to-interval conversion algorithms to allow use of parametric statistics for domain scores with and without national items.

| S-EPMC5094704 | biostudies-literature

Resilience in relation to personality and intelligence.

Project description:Resilience is a construct of increasing interest, but validated scales measuring resilience factors among adults are scarce. Here, a scale named the Resilience Scale for Adults (RSA) was crossvalidated and compared with measures of personality (Big Five/5PFs), cognitive abilities (Raven's Advanced Matrices, Vocabulary, Number series), and social intelligence (TSIS). All measures were given to 482 applicants for the military college. Confirmatory factor analyses confirmed the fit of the five-factor model, measuring 'personal strength', 'social competence', 'structured style', 'family cohesion' and 'social resources'. Using Big Five to discriminate between well adjusted and more vulnerable personality profiles, all resilience factors were positively correlated with the well adjusted personality profile. RSA-personal strength was most associated with 5PFs-emotional stability, RSA-social competence with 5PFs-extroversion and 5PFs-agreeableness, as well as TSIS-social skills, RSA-structured style with 5PFs-conscientiousness. Unexpectedly but interestingly, measures of RSA-family cohesion and RSA-social resources were also related to personality. Furthermore, the RSA was unrelated to cognitive abilities. This study supported the convergent and discriminative validity of the scale, and thus the inference that individuals scoring high on this scale are psychologically healthier, better adjusted, and thus more resilient.

| S-EPMC6878482 | biostudies-literature

Pelvic organ prolapse symptoms in relation to POPQ, ordinal stages and ultrasound prolapse assessment.

Project description:Adequate staging of pelvic organ prolapse is important in clinical practice and research. The ability of the POPQ, ordinal stages and ultrasound prolapse assessment were evaluated for their ability to discriminate between women with and without prolapse symptoms. The leading edge of the predominant compartment in the three assessment systems was used for the calculation of receiver operating characteristics curves. Two hundred and sixty five (265) consecutive women were evaluated. The area under the receiver operating characteristics curve for the three staging systems ranged from 0.715 to 0.783. POPQ staging and ordinal staging performed equally well in the prediction of prolapse symptoms (p = 0.780), and both performed better as compared with ultrasound prolapse assessment (p = 0.048 and p = 0.015, respectively). Prolapse staging can equally be performed by the POPQ and ordinal stages systems as far as the discrimination between women with and without prolapse symptoms is concerned. The ultrasound prolapse assessment does not perform better as compared with these two systems.

| S-EPMC2515548 | biostudies-other

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data