Control Function Assisted IPW Estimation with a Secondary Outcome in Case-Control Studies

Case-control studies are designed towards studying associations between risk factors and a single, primary outcome. Information about additional, secondary outcomes is also collected, but association studies targeting such secondary outcomes should account for the case-control sampling scheme, or otherwise results may be biased. Often, one uses inverse probability weighted (IPW) estimators to estimate population effects in such studies. However, these estimators are inefficient relative to estimators that make additional assumptions about the data generating mechanism. We propose a class of estimators for the effect of risk factors on a secondary outcome in case-control studies, when the mean is modeled using either the identity or the log link. The proposed estimator combines IPW with a mean zero control function that depends explicitly on a model for the primary disease outcome. The efficient estimator in our class of estimators reduces to standard IPW when the model for the primary disease outcome is unrestricted, and is more efficient than standard IPW when the model is either parametric or semiparametric

Трехизбенский городок в исторических источниках

Contains fulltext : 137371.pdf (publisher's version ) (Closed access)The role of face typicality in face recognition is well established, but it is unclear whether face typicality is important for face evaluation. Prior studies have focused mainly on typicality's influence on attractiveness, although recent studies have cast doubt on its importance for attractiveness judgments. Here, we argue that face typicality is an important factor for social perception because it affects trustworthiness judgments, which approximate the basic evaluation of faces. This effect has been overlooked because trustworthiness and attractiveness judgments have a high level of shared variance for most face samples. We show that for a continuum of faces that vary on a typicality-attractiveness dimension, trustworthiness judgments peak around the typical face. In contrast, perceived attractiveness increases monotonically past the typical face, as faces become more like the most attractive face. These findings suggest that face typicality is an important determinant of face evaluation.9 p

Bargaining, Compensating Wage Differentials, and Dualism of the Labor Market: Theory and Evidence from France

The theory of compensating differentials predicts a negative relationship between wages and good working conditions, while the theory of segmentation predicts a positive one. Combining the hedonic wage model and the wages‐employment collective bargaining model, we show the relevance of a further factor: a union power effect. Then we test the validity of this effect with French cross‐section data. Empirical results confirm the predictions of the model, that is, the coexistence of a negative relationship between wages and good working conditions for the whole sample (market effect) and a positive relationship in highly unionized sectors (union power effect)

Microscopic parameters of the van der Waals CrSBr antiferromagnet from microwave absorption experiments

Microwave absorption experiments employing a phase-sensitive external resistive detection are performed for a topical van der Waals antiferromagnet CrSBr. The field dependence of two resonance modes is measured in an applied field parallel to the three principal crystallographic directions, revealing anisotropies and magnetic transitions in this material. To account for the observed results, we formulate a microscopic spin model with a bi-axial single-ion anisotropy and inter-plane exchange. Theoretical calculations give an excellent description of full magnon spectra enabling us to precisely determine microscopic interaction parameters for CrSBr.Comment: includes a supplementary information documen

Postextubation pulmonary edema: A case series and review

SummaryWe report a series of patients with postextubation pulmonary edema who had no obvious risk factors for the development of this syndrome.MethodsPatients identified by the pulmonary consultation service at an academic medical center were reviewed.ResultsFourteen cases were collected and analyzed. The average age was 34.5 years; 12 patients were male. The average BMI was 25.5. None had documented previous lung disease. Most operations were scheduled as outpatient procedures, and the type of surgery ranged from an incision and drainage of a bite wound to an open reduction- internal fixation of the radius. None of the patients had upper airway surgery. The length of surgeries ranged from 27 to 335min. Laryngospasm was the most commonly identified obstructing event postextubation. Treatment involved airway support when needed, supplemental oxygen, and diuretics.ConclusionsIt would appear that all patients, especially young men, are at risk for the development of this syndrome and that the pathogenesis remains uncertain in many cases

A Powerful Statistical Framework for Generalization Testing in GWAS, with Application to the HCHS/SOL

In GWAS, “generalization” is the replication of genotype-phenotype association in a population with different ancestry than the population in which it was first identified. The standard for reporting findings from a GWAS requires a two-stage design, in which discovered associations are replicated in an independent follow-up study. Current practices for declaring generalizations rely on testing associations while controlling the Family Wise Error Rate (FWER) in the discovery study, then separately controlling error measures in the follow-up study. While this approach limits false generalizations, we show that it does not guarantee control over the FWER or False Discovery Rate (FDR) of the generalization null hypotheses. In addition, it fails to leverage the two-stage design to increase power for detecting generalized associations. We develop a formal statistical framework for quantifying the evidence of generalization that accounts for the (in)consistency between the directions of associations in the discovery and follow-up studies. We develop the directional generalization FWER (FWERg) and FDR (FDRg) controlling r-values, which are used to declare associations as generalized. This framework extends to generalization testing when applied to a published list of SNP-trait associations. We show that our framework accommodates various SNP selection rules for generalization testing based on p-values in the discovery study, and still control FWERg or FDRg. A key finding is that it is often beneficial to use a more lenient p-value threshold then the genome-wide significance threshold. For instance, in a GWAS of Total Cholesterol (TC) in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), when testing all SNPs with p-values\u3c 5 × 10−8 (15 genomic regions) for generalization in a large GWAS of whites, we generalized SNPs from 15 regions. But when testing all SNPs with p-values\u3c 6.6×10−5 (89 regions), we generalized SNPs from 27 regions

Gender divisions of domestic labour and paid domestic services

This article investigates the relationship between sharing domestic tasks in dual-earner mixed-sex couples and using of paid domestic services. Results from a small-scale survey of the domestic outsourcing practices of employees of a large service-sector organisation in the UK show that in households: full-time working by women and presence of younger children is positively associated with using of domestic services; there is no association between the gender division of traditionally female domestic tasks carried out within the couple and paid services; in contrast, men’s greater involvement in traditionally male and traditionally gender-neutral tasks is positively associating with using paid domestic services. These findings tentatively suggest a new arrangement may be emerging whereby some couples address a heavy workload and desire for a less traditional division of domestic labour by men participating more in close-ended domestic tasks and outsourcing more time-consuming tasks traditionally undertaken by women to paid service providers

Variant-specific inflation factors for assessing population stratification at the phenotypic variance level

In modern Whole Genome Sequencing (WGS) epidemiological studies, participant-level data from multiple studies are often pooled and results are obtained from a single analysis. We consider the impact of differential phenotype variances by study, which we term \u27variance stratification\u27. Unaccounted for, variance stratification can lead to both decreased statistical power, and increased false positives rates, depending on how allele frequencies, sample sizes, and phenotypic variances vary across the studies that are pooled. We develop a procedure to compute variant-specific inflation factors, and show how it can be used for diagnosis of genetic association analyses on pooled individual level data from multiple studies. We describe a WGS-appropriate analysis approach, implemented in freely-available software, which allows study-specific variances and thereby improves performance in practice. We illustrate the variance stratification problem, its solutions, and the proposed diagnostic procedure, in simulations and in data from the Trans-Omics for Precision Medicine Whole Genome Sequencing Program (TOPMed), used in association tests for hemoglobin concentrations and BMI

Associations Between \u3cem\u3eSLC16A11\u3c/em\u3e Variants and Diabetes in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

Five sequence variants in SLC16A11 (rs117767867, rs13342692, rs13342232, rs75418188, and rs75493593), which occur in two non-reference haplotypes, were recently shown to be associated with diabetes in Mexicans from the SIGMA consortium. We aimed to determine whether these previous findings would replicate in the HCHS/SOL Mexican origin group and whether genotypic effects were similar in other HCHS/SOL groups. We analyzed these five variants in 2492 diabetes cases and 5236 controls from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), which includes U.S. participants from six diverse background groups (Mainland groups: Mexican, Central American, and South American; and Caribbean groups: Puerto Rican, Cuban, and Dominican). We estimated the SNP-diabetes association in the six groups and in the combined sample. We found that the risk alleles occur in two non-reference haplotypes in HCHS/SOL, as in the SIGMA Mexicans. The haplotype frequencies were very similar between SIGMA Mexicans and the HCHS/SOL Mainland groups, but different in the Caribbean groups. The SLC16A11 sequence variants were significantly associated with risk for diabetes in the Mexican origin group (P = 0.025), replicating the SIGMA findings. However, these variants were not significantly associated with diabetes in a combined analysis of all groups, although the power to detect such effects was 85% (assuming homogeneity of effects among the groups). Additional analyses performed separately in each of the five non-Mexican origin groups were not significant. We also analyzed (1) exclusion of young controls and, (2) SNP by BMI interactions, but neither was significant in the HCHS/SOL data. The previously reported effects of SLC16A11 variants on diabetes in Mexican samples was replicated in a large Mexican-American sample, but these effects were not significant in five non-Mexican Hispanic/Latino groups sampled from U.S. populations. Lack of replication in the HCHS/SOL non-Mexicans, and in the entire HCHS/SOL sample combined may represent underlying genetic heterogeneity. These results indicate a need for future genetic research to consider heterogeneity of the Hispanic/Latino population in the assessment of disease risk, but add to the evidence suggesting SLC16A11 as a potential therapeutic target for type 2 diabetes