lordif: An R Package for Detecting Differential Item Functioning Using Iterative Hybrid Ordinal Logistic Regression/Item Response Theory and Monte Carlo Simulations

Logistic regression provides a flexible framework for detecting various types of differential item functioning (DIF). Previous efforts extended the framework by using item response theory (IRT) based trait scores, and by employing an iterative process using group--specific item parameters to account for DIF in the trait scores, analogous to purification approaches used in other DIF detection frameworks. The current investigation advances the technique by developing a computational platform integrating both statistical and IRT procedures into a single program. Furthermore, a Monte Carlo simulation approach was incorporated to derive empirical criteria for various DIF statistics and effect size measures. For purposes of illustration, the procedure was applied to data from a questionnaire of anxiety symptoms for detecting DIF associated with age from the Patient--Reported Outcomes Measurement Information System.

Thermal activation energy of 3D vortex matter in NaFe1-xCoxAs (x=0.01, 0.03 and 0.07) single crystals

We report on the thermally activated flux flow dependency on the doping dependent mixed state in NaFe1-xCoxAs (x=0.01, 0.03, and 0.07) crystals using the magnetoresistivity in the case of B//c-axis and B//ab-plane. It was found clearly that irrespective of the doping ratio, magnetoresistivity showed a distinct tail just above the Tc, offset associated with the thermally activated flux flow (TAFF) in our crystals. Furthermore, in TAFF region the temperature dependence of the activation energy follows the relation U(T, B)=U_0 (B) (1-T/T_c )^q with q=1.5 in all studied crystals. The magnetic field dependence of the activation energy follows a power law of U_0 (B)~B^(-{\alpha}) where the exponent {\alpha} is changed from a low value to a high value at a crossover field of B=~2T, indicating the transition from collective to plastic pinning in the crystals. Finally, it is suggested that the 3D vortex phase is the dominant phase in the low-temperature region as compared to the TAFF region in our series samples

lordif: An R Package for Detecting Differential Item Functioning Using Iterative Hybrid Ordinal Logistic Regression/Item Response Theory and Monte Carlo Simulations

Logistic regression provides a flexible framework for detecting various types of differential item functioning (DIF). Previous efforts extended the framework by using item response theory (IRT) based trait scores, and by employing an iterative process using group--specific item parameters to account for DIF in the trait scores, analogous to purification approaches used in other DIF detection frameworks. The current investigation advances the technique by developing a computational platform integrating both statistical and IRT procedures into a single program. Furthermore, a Monte Carlo simulation approach was incorporated to derive empirical criteria for various DIF statistics and effect size measures. For purposes of illustration, the procedure was applied to data from a questionnaire of anxiety symptoms for detecting DIF associated with age from the Patient--Reported Outcomes Measurement Information System

A Two-Level Adaptive Test Battery

A test battery with two different levels of adaptation is presented: a within-subtest level for the selection of the items in the subtests and a between-subtest level to move from one subtest to the next. The battery runs on a two-level model consisting of a regular response model for each of the subtests extended with a second level for the joint distribution of their abilities. The presentation of the model is followed by an optimized MCMC algorithm to update the posterior distribution of each of its ability parameters, select the items to Bayesian optimality, and adaptively move from one subtest to the next. Thanks to extremely rapid convergence of the Markov chain and simple posterior calculations, the algorithm can be used in real-world applications without any noticeable latency. Finally, an empirical study with a battery of short diagnostic subtests is shown to yield score accuracies close to traditional one-level adaptive testing with subtests of double lengths.</p

Development of a Conceptual Framework and Calibrated Item Banks to Measure Patient-Reported Dyspnea Severity and Related Functional Limitations

AbstractObjectivesChronic obstructive pulmonary disease is a major global health problem. Although several patient-reported outcome (PRO) measures of chronic obstructive pulmonary disease exist, none were developed using patient-driven concept development. We developed an item bank for dyspnea severity and related functional limitations on the basis of a PRO conceptual framework derived from patient input.MethodsWe identified a large pool of existing items based on a conceptual framework and literature review. Using patient and expert review panels and an item refinement/modification process, we developed an item bank aligned with the conceptual framework, which subsequently underwent psychometric testing via an online Internet panel of dyspnea patients (N = 608).ResultsExploratory factor analysis suggested a dominant first factor accounting for about 78% of the total variance. Confirmatory factor analysis supported a unidimensional model. Item response theory analysis demonstrated good model fit, and differential item functioning analyses indicated that the 33-item scale showed potential for measurement equivalence across sex. A 10-item short form produced comparable scores (r = 0.98) and a computerized adaptive-testing simulation indicated efficient measurement with fewer items (mean 4.65 items).ConclusionsAn efficient patient-reported measure of dyspnea severity and related functional limitations, based on a patient-driven PRO conceptual framework, is now available for further validation and use

Psychometric characteristics of daily diaries for the Patient-Reported Outcomes Measurement Information System (PROMIS®): a preliminary investigation

Purpose - The Patient-Reported Outcomes (PRO) Measurement Information System (PROMIS®) has developed assessment tools for numerous PROs, most using a 7-day recall format. We examined whether modifying the recall period for use in daily diary research would affect the psychometric characteristics of several PROMIS measures. Methods - Daily versions of short-forms for three PROMIS domains (pain interference, fatigue, depression) were administered to a general population sample (n = 100) for 28 days. Analyses used multilevel item response theory (IRT) models. We examined differential item functioning (DIF) across recall periods by comparing the IRT parameters from the daily data with the PROMIS 7-day recall IRT parameters. Additionally, we examined whether the IRT parameters for day-to-day within-person changes are invariant to those for between-person (cross-sectional) differences in PROs. Results - Dimensionality analyses of the daily data suggested a single dimension for each PRO domain, consistent with PROMIS instruments. One-third of the daily items showed uniform DIF when compared with PROMIS 7-day recall, but the impact of DIF on the scale level was minor. IRT parameters for within-person changes differed from between-person parameters for 3 depression items, which were more sensitive for measuring change than between-person differences, but not for pain interference and fatigue items. Notably, mean scores from daily diaries were significantly lower than the PROMIS 7-day recall norms. Conclusions - The results provide initial evidence supporting the adaptation of PROMIS measures for daily diary research. However, scores from daily diaries cannot be directly interpreted on PROMIS norms established for 7-day recall

The cap-snatching SFTSV endonuclease domain is an antiviral target

Severe fever with thrombocytopenia syndrome virus (SFTSV) is a tick-borne virus with 12%-30% case mortality rates and is related to the Heartland virus (HRTV) identified in the United States. Together, SFTSV and HRTV are emerging segmented, negative-sense RNA viral (sNSV) pathogens with potential global health impact. Here, we characterize the amino-terminal cap-snatching endonuclease domain of SFTSV polymerase (L) and solve a 2.4-Å X-ray crystal structure. While the overall structure is similar to those of other cap-snatching sNSV endonucleases, differences near the C terminus of the SFTSV endonuclease suggest divergence in regulation. Influenza virus endonuclease inhibitors, including the US Food and Drug Administration (FDA) approved Baloxavir (BXA), inhibit the endonuclease activity in in vitro enzymatic assays and in cell-based studies. BXA displays potent activity with a half maximal inhibitory concentration (I

Using linkage analysis of large pedigrees to guide association analyses

To date, genome-wide association studies have yielded discoveries of common variants that partly explain familial aggregation of diseases and traits. Researchers are now turning their attention to less common variants because the price of sequencing has dropped drastically. However, because sequencing of the whole genome in large samples is costly, great care must be taken to prioritize which samples and which genomic regions are selected for sequencing. We are interested in identifying genomic regions for deep sequencing using large multiplex families collected as part of earlier linkage studies. We incorporate linkage analysis into our search for Q1-associated alleles. Overall, we found that power was low for both whole-exome and linkage-guided sequencing analysis. By restricting sequencing to regions with high LOD peaks, we found fewer associated single-nucleotide polymorphisms than by using whole-exome sequencing. However, incorporating linkage analysis enabled us to detect more than half of the associated susceptibility loci (52%) that would have been identified by whole-exome sequencing while examining only 2.5% of the exome. This result suggests that incorporating linkage results from large multiplex families might greatly increase the efficiency of sequencing to detect trait-associated alleles in complex disease

Effectiveness of iron supplementation in the perioperative management of total knee arthroplasty: a systematic review

Abstract Introduction/purpose The purpose of this systematic review was to evaluate the effect of iron supplementation during total knee arthroplasty (TKA): (1) Is the iron supplementation necessary during TKA? (2) When is the optimal timing of iron supplementation? (3) Which is better, between orally and intravenously administered iron supplementation? And (4) What is the optimal dose of iron supplementation? Materials and methods A rigorous and systematic approach was used and each of the selected studies was evaluated for methodological quality. Data about study design, total number of cases enrolled, iron administration method, timing, and dose were extracted. Change in hemoglobin and transfusion rates were extracted to evaluate the effectiveness of iron supplementation. Results Eleven studies were included in the final analysis. Most of studies reported that hemoglobin change between iron and control group did not show any difference. Only one study reported that iron supplementation could reduce the decrease in hemoglobin. However, transfusion rate showed a decrease in the iron supplementation group compared with the control group. There was no clear consensus on the optimum timing and dose of iron supplementation and intravenously administered iron was more effective than orally administered iron, especially in anemic patients. Conclusion Iron supplementation is not clear as a way to raise hemoglobin levels after TKA, but an effective treatment for lowering transfusion rate, especially in patients with anemia. We could not determine the optimal timing and dose of the iron. Intravenously administered iron was similar to, or better than, orally administered iron for improving hemoglobin levels and transfusion rate