School ties: An analysis of homophily in an adolescent friendship network

Homophily is the tendency to establish relationships among people who share similar characteristics or attributes. This study presents evidence of homophilic behaviour for an adolescent friendship network of 6,961 links in the West of England. We control for unobserved characteristics by estimating school and individual fixed effects and present evidence on the role of length and closeness of friendships on the degree of homophily. We also exploit the dynamics of the friendship by comparing similarities among existing and future friends. Results indicate that academic achievement, personality, educational aspirations, bad behaviour and mother’s education are essential in the friendship formation process. However, income and parents’ occupational class proved to be insignificant. We also show that the degree of homophily among friends selected from a random process is much lower than that of the observed friendships.Networks, Homophily, Segregation, Friendships, Adolescents

A Weak Instrument F-Test in Linear IV Models with Multiple Endogenous Variables

AbstractWe consider testing for weak instruments in a model with multiple endogenous variables. Unlike Stock and Yogo (2005), who considered a weak instruments problem where the rank of the matrix of reduced form parameters is near zero, here we consider a weak instruments problem of a near rank reduction of one in the matrix of reduced form parameters. For example, in a two-variable model, we consider weak instrument asymptotics of the form π1=δπ2+c/n where π1 and π2 are the parameters in the two reduced-form equations, c is a vector of constants and n is the sample size. We investigate the use of a conditional first-stage F-statistic along the lines of the proposal by Angrist and Pischke (2009) and show that, unless δ=0, the variance in the denominator of their F-statistic needs to be adjusted in order to get a correct asymptotic distribution when testing the hypothesis H0:π1=δπ2. We show that a corrected conditional F-statistic is equivalent to the Cragg and Donald (1993) minimum eigenvalue rank test statistic, and is informative about the maximum total relative bias of the 2SLS estimator and the Wald tests size distortions. When δ=0 in the two-variable model, or when there are more than two endogenous variables, further information over and above the Cragg–Donald statistic can be obtained about the nature of the weak instrument problem by computing the conditional first-stage F-statistics

BECOMING RESEARCHED: THE OPPORTUNITIES OF AUTOETHNOGRAPHY IN TOURISM RESEARCH

This paper explores the concept of ‘becoming researched’ through the opportunities for autoethnography as a technique of data collection. This research emerges from both authors’ PhD research experiences and explores the ways in which autoethnography mobilises an appreciation for the embodied, sensual and emotional experiences of tourist and research practice. As such, it proposes communication through inter-subjective negotiation and facilitates an enriched research space within which previously ‘hidden’ spaces emerge through stimulating creativity and deepening connection through mutual appreciation between researcher and participants

Testing and correcting for weak and pleiotropic instruments in two-sample multivariable Mendelian randomization

Multivariable Mendelian randomization (MVMR) is a form of instrumental variable analysis which estimates the direct effect of multiple exposures on an outcome using genetic variants as instruments. Mendelian randomization and MVMR are frequently conducted using two‐sample summary data where the association of the genetic variants with the exposures and outcome are obtained from separate samples. If the genetic variants are only weakly associated with the exposures either individually or conditionally, given the other exposures in the model, then standard inverse variance weighting will yield biased estimates for the effect of each exposure. Here, we develop a two‐sample conditional F‐statistic to test whether the genetic variants strongly predict each exposure conditional on the other exposures included in a MVMR model. We show formally that this test is equivalent to the individual level data conditional F‐statistic, indicating that conventional rule‐of‐thumb critical values of [Formula: see text] 10, can be used to test for weak instruments. We then demonstrate how reliable estimates of the causal effect of each exposure on the outcome can be obtained in the presence of weak instruments and pleiotropy, by repurposing a commonly used heterogeneity Q‐statistic as an estimating equation. Furthermore, the minimized value of this Q‐statistic yields an exact test for heterogeneity due to pleiotropy. We illustrate our methods with an application to estimate the causal effect of blood lipid fractions on age‐related macular degeneration

Chronic inflammation does not mediate the effect of adiposity on grip strength: results from a multivariable Mendelian randomization study

The relationship between adiposity and grip strength (GS) is complex. We investigated whether one pathway through which adiposity affects GS was via chronic inflammation. 367,583 UK Biobank participants had body mass index (BMI), waist-hip-ratio (WHR), C-reactive protein (CRP) and GS data. Univariable Mendelian randomization (MR) and multivariable Mendelian randomization (MVMR) analyses (using inverse variance weighted (IVW) weighted median estimates (WME) and MR-Egger models) estimated total, direct and indirect effects of adiposity traits on GS using genetic instruments for BMI and WHR (exposures) and CRP (mediator). Observational findings suggested higher BMI was associated with stronger grip, e.g., in males, per standard deviation (SD) higher BMI, GS was higher by 0.48 kg (95% confidence interval(CI):0.44,0.51), independent of CRP. For males MR estimates were directionally consistent; for females, estimates were consistent with the null. Observational findings for WHR suggested that higher WHR was associated with weaker grip. In multivariable MR-IVW analyses, effects in males were consistent with the null. In females, there were consistent effects such that higher WHR was associated with stronger grip, e.g., 1-SD higher WHR was associated with 1.25 kg (MVMR-Egger; 95% CI:0.72,1.78) stronger grip, independent of CRP. Across sexes and adiposity indicators, CRP’s mediating role was minor. Greater adiposity may increase GS in early old age, but effects vary by sex and adiposity location. There was no evidence that inflammation mediated these effects

A guide for understanding and designing Mendelian randomization studies in the musculoskeletal field

Mendelian randomization (MR) is an increasingly popular component of an epidemiologist's toolkit, used to provide evidence of a causal effect of one trait (an exposure, eg, body mass index [BMI]) on an outcome trait or disease (eg, osteoarthritis). Identifying these effects is important for understanding disease etiology and potentially identifying targets for therapeutic intervention. MR uses genetic variants as instrumental variables for the exposure, which should not be influenced by the outcome or confounding variables, overcoming key limitations of traditional epidemiological analyses. For MR to generate a valid estimate of effect, key assumptions must be met. In recent years, there has been a rapid rise in MR methods that aim to test, or are robust to violations of, these assumptions. In this review, we provide an overview of MR for a non‐expert audience, including an explanation of these key assumptions and how they are often tested, to aid a better reading and understanding of the MR literature. We highlight some of these new methods and how they can be useful for specific methodological challenges in the musculoskeletal field, including for conditions or traits that share underlying biological pathways, such as bone and joint disease. © 2022 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research

The impact of education inequality on rheumatoid arthritis risk is mediated by smoking and body mass index: mendelian randomization study

Objective To estimate the causal relationship between educational attainment—as a proxy for socioeconomic inequality—and risk of RA, and quantify the roles of smoking and BMI as potential mediators. Methods Using the largest genome-wide association studies (GWAS), we performed a two‐sample Mendelian randomization (MR) study of genetically predicted educational attainment (instrumented using 1265 variants from 766 345 individuals) and RA (14 361 cases, 43 923 controls). We used two-step MR to quantify the proportion of education’s effect on RA mediated by smoking exposure (as a composite index capturing duration, heaviness and cessation, using 124 variants from 462 690 individuals) and BMI (517 variants, 681 275 individuals), and multivariable MR to estimate proportion mediated by both factors combined. Results Each S.D. increase in educational attainment (4.2 years of schooling) was protective of RA (odds ratio 0.37; 95% CI: 0.31, 0.44). Higher educational attainment was also protective for smoking exposure (β = −0.25 S.D.; 95% CI: −0.26, −0.23) and BMI [β = −0.27 S.D. (∼1.3 kg/m2); 95% CI: −0.31, −0.24]. Smoking mediated 24% (95% CI: 13%, 35%) and BMI 17% (95% CI: 11%, 23%) of the total effect of education on RA. Combined, the two risk factors explained 47% (95% CI: 11%, 82%) of the total effect. Conclusion Higher educational attainment has a protective effect on RA risk. Interventions to reduce smoking and excess adiposity at a population level may reduce this risk, but a large proportion of education’s effect on RA remains unexplained. Further research into other risk factors that act as potentially modifiable mediators are required