57 research outputs found

    Impact of an equality constraint on the class-specific residual variances in regression mixtures:a Monte Carlo simulation study

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    Regression mixture models are a novel approach to modeling the heterogeneous effects of predictors on an outcome. In the model-building process, often residual variances are disregarded and simplifying assumptions are made without thorough examination of the consequences. In this simulation study, we investigated the impact of an equality constraint on the residual variances across latent classes. We examined the consequences of constraining the residual variances on class enumeration (finding the true number of latent classes) and on the parameter estimates, under a number of different simulation conditions meant to reflect the types of heterogeneity likely to exist in applied analyses. The results showed that bias in class enumeration increased as the difference in residual variances between the classes increased. Also, an inappropriate equality constraint on the residual variances greatly impacted on the estimated class sizes and showed the potential to greatly affect the parameter estimates in each class. These results suggest that it is important to make assumptions about residual variances with care and to carefully report what assumptions are made

    Using multilevel regression mixture models to identify level-1 heterogeneity in level-2 effects

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    This article proposes a novel exploratory approach for assessing how the effects of Level-2 predictors differ across Level-1 units. Multilevel regression mixture models are used to identify latent classes at Level 1 that differ in the effect of 1 or more Level-2 predictors. Monte Carlo simulations are used to demonstrate the approach with different sample sizes and to demonstrate the consequences of constraining 1 of the random effects to 0. An application of the method to evaluate heterogeneity in the effects of classroom practices on students is used to show the types of research questions that can be answered with this method and the issues faced when estimating multilevel regression mixtures

    Evaluating differential effects using regression interactions and regression mixture models

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    Research increasingly emphasizes understanding differential effects. This article focuses on understanding regression mixture models, which are relatively new statistical methods for assessing differential effects by comparing results to using an interactive term in linear regression. The research questions which each model answers, their formulation, and their assumptions are compared using Monte Carlo simulations and real data analysis. The capabilities of regression mixture models are described and specific issues to be addressed when conducting regression mixtures are proposed. The article aims to clarify the role that regression mixtures can take in the estimation of differential effects and increase awareness of the benefits and potential pitfalls of this approach. Regression mixture models are shown to be a potentially effective exploratory method for finding differential effects when these effects can be defined by a small number of classes of respondents who share a typical relationship between a predictor and an outcome. It is also shown that the comparison between regression mixture models and interactions becomes substantially more complex as the number of classes increases. It is argued that regression interactions are well suited for direct tests of specific hypotheses about differential effects and regression mixtures provide a useful approach for exploring effect heterogeneity given adequate samples and study design

    The effects of sample size on the estimation of regression mixture models

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    Regression mixture models are a statistical approach used for estimating heterogeneity in effects. This study investigates the impact of sample size on regression mixture’s ability to produce “stable” results. Monte Carlo simulations and analysis of resamples from an application data set were used to illustrate the types of problems that may occur with small samples in real data sets. The results suggest that (a) when class separation is low, very large sample sizes may be needed to obtain stable results; (b) it may often be necessary to consider a preponderance of evidence in latent class enumeration; (c) regression mixtures with ordinal outcomes result in even more instability; and (d) with small samples, it is possible to obtain spurious results without any clear indication of there being a problem

    What does it mean to be affiliated with care?: Delphi consensus on the definition of unaffiliation and specialist in sickle cell disease

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    Accruing evidence reveals best practices for how to help individuals living with Sickle Cell Disease (SCD); yet, the implementation of these evidence-based practices in healthcare settings is lacking. The Sickle Cell Disease Implementation Consortium (SCDIC) is a national consortium that uses implementation science to identify and address barriers to care in SCD. The SCDIC seeks to understand how and why patients become unaffiliated from care and determine strategies to identify and connect patients to care. A challenge, however, is the lack of agreed-upon definition for what it means to be unaffiliated and what it means to be a SCD expert provider . In this study, we conducted a Delphi process to obtain expert consensus on what it means to be an unaffiliated patient with SCD and to define an SCD specialist, as no standard definition is available. Twenty-eight SCD experts participated in three rounds of questions. Consensus was defined as 80% or more of respondents agreeing. Experts reached consensus that an individual with SCD who is unaffiliated from care is someone who has not been seen by a sickle cell specialist in at least a year. A sickle cell specialist was defined as someone with knowledge and experience in SCD. Having knowledge means: being knowledgeable of the 2014 NIH Guidelines, Evidence-Based Management of SCD , trained in hydroxyurea management and transfusions, trained on screening for organ damage in SCD, trained in pain management and on SCD emergencies, and is aware of psychosocial and cognitive issues in SCD. Experiences that are expected of a SCD specialist include experience working with SCD patients, mentored by a SCD specialist, regular attendance at SCD conferences, and obtains continuing medical education on SCD every 2 years. The results have strong implications for future research, practice, and policy related to SCD by helping to lay a foundation for an new area of research (e.g., to identify subpopulations of unaffiliation and targeted interventions) and policies that support reaffiliation and increase accessibility to quality care

    Development of a Comprehensive Measure of Organizational Readiness (Motivation × Capacity) For Implementation: A Study Protocol

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    BACKGROUND: Organizational readiness is important for the implementation of evidence-based interventions. Currently, there is a critical need for a comprehensive, valid, reliable, and pragmatic measure of organizational readiness that can be used throughout the implementation process. This study aims to develop a readiness measure that can be used to support implementation in two critical public health settings: federally qualified health centers (FQHCs) and schools. The measure is informed by the Interactive Systems Framework for Dissemination and Implementation and R = MC heuristic (readiness = motivation × innovation-specific capacity × general capacity). The study aims are to adapt and further develop the readiness measure in FQHCs implementing evidence-based interventions for colorectal cancer screening, to test the validity and reliability of the developed readiness measure in FQHCs, and to adapt and assess the usability and validity of the readiness measure in schools implementing a nutrition-based program. METHODS: For aim 1, we will conduct a series of qualitative interviews to adapt the readiness measure for use in FQHCs. We will then distribute the readiness measure to a developmental sample of 100 health center sites (up to 10 staff members per site). We will use a multilevel factor analysis approach to refine the readiness measure. For aim 2, we will distribute the measure to a different sample of 100 health center sites. We will use multilevel confirmatory factor analysis models to examine the structural validity. We will also conduct tests for scale reliability, test-retest reliability, and inter-rater reliability. For aim 3, we will use a qualitative approach to adapt the measure for use in schools and conduct reliability and validity tests similar to what is described in aim 2. DISCUSSION: This study will rigorously develop a readiness measure that will be applicable across two settings: FQHCs and schools. Information gained from the readiness measure can inform planning and implementation efforts by identifying priority areas. These priority areas can inform the selection and tailoring of support strategies that can be used throughout the implementation process to further improve implementation efforts and, in turn, program effectiveness

    Selective Caries Removal in Permanent Teeth (SCRiPT) for the treatment of deep carious lesions:a randomised controlled clinical trial in primary care

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    Background Dental caries is one of the most prevalent non-communicable disease globally and can have serious health sequelae impacting negatively on quality of life. In the UK most adults experience dental caries during their lifetime and the 2009 Adult Dental Health Survey reported that 85% of adults have at least one dental restoration. Conservative removal of tooth tissue for both primary and secondary caries reduces the risk of failure due to tooth-restoration, complex fracture as well as remaining tooth surfaces being less vulnerable to further caries. However, despite its prevalence there is no consensus on how much caries to remove prior to placing a restoration to achieve optimal outcomes. Evidence for selective compared to complete or near-complete caries removal suggests there may be benefits for selective removal in sustaining tooth vitality, therefore avoiding abscess formation and pain, so eliminating the need for more complex and costly treatment or eventual tooth loss. However, the evidence is of low scientific quality and mainly gleaned from studies in primary teeth. Method This is a pragmatic, multi-centre, two-arm patient randomised controlled clinical trial including an internal pilot set in primary dental care in Scotland and England. Dental health professionals will recruit 623 participants over 12-years of age with deep carious lesions in their permanent posterior teeth. Participants will have a single tooth randomised to either the selective caries removal or complete caries removal treatment arm. Baseline measures and outcome data (during the 3-year follow-up period) will be assessed through clinical examination, patient questionnaires and NHS databases. A mixed-method process evaluation will complement the clinical and economic outcome evaluation and examine implementation, mechanisms of impact and context. The primary outcome at three years is sustained tooth vitality. The primary economic outcome is net benefit modelled over a lifetime horizon. Clinical secondary outcomes include pulp exposure, progession of caries, restoration failure; as well as patient-centred and economic outcomes. Discussion SCRiPT will provide evidence for the most clinically effective and cost-beneficial approach to managing deep carious lesions in permanent posterior teeth in primary care. This will support general dental practitioners, patients and policy makers in decision making. Trial Registration Trial registry: ISRCTN. Trial registration number: ISRCTN76503940. Date of Registration: 30.10.2019

    A genetic variation map for chicken with 2.8 million single-nucleotide polymorphisms

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    We describe a genetic variation map for the chicken genome containing 2.8 million single-nucleotide polymorphisms ( SNPs). This map is based on a comparison of the sequences of three domestic chicken breeds ( a broiler, a layer and a Chinese silkie) with that of their wild ancestor, red jungle fowl. Subsequent experiments indicate that at least 90% of the variant sites are true SNPs, and at least 70% are common SNPs that segregate in many domestic breeds. Mean nucleotide diversity is about five SNPs per kilobase for almost every possible comparison between red jungle fowl and domestic lines, between two different domestic lines, and within domestic lines - in contrast to the notion that domestic animals are highly inbred relative to their wild ancestors. In fact, most of the SNPs originated before domestication, and there is little evidence of selective sweeps for adaptive alleles on length scales greater than 100 kilobases

    Structural basis of PROTAC cooperative recognition for selective protein degradation

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    Inducing macromolecular interactions with small molecules to activate cellular signaling is a challenging goal. PROTACs (proteolysis-targeting chimeras) are bifunctional molecules that recruit a target protein in proximity to an E3 ubiquitin ligase to trigger protein degradation. Structural elucidation of the key ternary ligase-PROTAC-target species and its impact on target degradation selectivity remain elusive. We solved the crystal structure of Brd4 degrader MZ1 in complex with human VHL and the Brd4 bromodomain (Brd4BD2). The ligand folds into itself to allow formation of specific intermolecular interactions in the ternary complex. Isothermal titration calorimetry studies, supported by surface mutagenesis and proximity assays, are consistent with pronounced cooperative formation of ternary complexes with Brd4BD2. Structure-based-designed compound AT1 exhibits highly selective depletion of Brd4 in cells. Our results elucidate how PROTAC-induced de novo contacts dictate preferential recruitment of a target protein into a stable and cooperative complex with an E3 ligase for selective degradation

    [Avian cytogenetics goes functional] Third report on chicken genes and chromosomes 2015

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    High-density gridded libraries of large-insert clones using bacterial artificial chromosome (BAC) and other vectors are essential tools for genetic and genomic research in chicken and other avian species... Taken together, these studies demonstrate that applications of large-insert clones and BAC libraries derived from birds are, and will continue to be, effective tools to aid high-throughput and state-of-the-art genomic efforts and the important biological insight that arises from them
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