On making causal claims: A review and recommendations

Social scientists often estimate models from correlational data, where the independent variable has not been exogenously manipulated; they also make implicit or explicit causal claims based on these models. When can these claims be made? We answer this question by first discussing design and estimation conditions under which model estimates can be interpreted, using the randomized experiment as the gold standard. We show how endogeneity--which includes omitted variables, omitted selection, simultaneity, common methods bias, and measurement error--renders estimates causally uninterpretable. Second, we present methods that allow researchers to test causal claims in situations where randomization is not possible or when causal interpretation is confounded, including fixed-effects panel, sample selection, instrumental variable, regression discontinuity, and difference-in-differences models. Third, we take stock of the methodological rigor with which causal claims are being made in a social sciences discipline by reviewing a representative sample of 110 articles on leadership published in the previous 10 years in top-tier journals. Our key finding is that researchers fail to address at least 66 % and up to 90 % of design and estimation conditions that make causal claims invalid. We conclude by offering 10 suggestions on how to improve non-experimental research.

Nonclassical measurement error with applications to labor and development issues

Zero correlation between measurement error and model error has been assumed in existing panel data models dealing specifically with measurement error. We extend this literature and propose a simple model where one regressor is mismeasured, allowing the measurement error to correlate with model error. Zero correlation between measurement error and model error is a special case in our model where correlated measurement error equals zero. We ask two research questions. First, we wonder if the correlated measurement error can be identified in the context of panel data. Second, we wonder if classical instrumental variables in panel data need to be adjusted when correlation between measurement error and model error cannot be ignored. Under some regularity conditions the answer is yes to both questions. We then propose a two-step estimation corresponding to the two questions. The first step estimates correlated measurement error from a reverse regression; and the second step estimates usual coefficients of interest using adjusted instruments.

The effect of retirement on cognitive functioning

Cognitive impairment has emerged as a major driver of disability in old age, with profound effects on individual well-being and decision making at older ages. In the light of policies aimed at postponing retirement ages, an important question is whether continued labour supply helps to maintain high levels of cognition at older ages. We use data of older men from the US Health and Retirement Study to estimate the effect of continued labour market participation at older ages on later-life cognition. As retirement itself is likely to depend on cognitive functioning and may thus be endogenous, we use offers of early retirement windows as instruments for retirement in econometric models for later-life cognitive functioning. These offers of early retirement are legally required to be nondiscriminatory and thus, inter alia, unrelated to cognitive functioning. At the same time, these offers of early retirement options are significant predictors of retirement. Although the simple ordinary least squares estimates show a negative relationship between retirement duration and various measures of cognitive functioning, instrumental variable estimates suggest that these associations may not be causal effects. Specifically, we find no clear relationship between retirement duration and later-life cognition for white-collar workers and, if anything, a positive relationship for blue-collar workers. Copyright © 2011 John Wiley & Sons, Ltd.

On making causal claims: A review and recommendations

Social scientists often estimate models from correlational data, where the independent variable has not been exogenously manipulated; they also make implicit or explicit causal claims based on these models. When can these claims be made? We answer this question by first discussing design and estimation conditions under which model estimates can be interpreted, using the randomized experiment as the gold standard. We show how endogeneity--which includes omitted variables, omitted selection, simultaneity, common methods bias, and measurement error--renders estimates causally uninterpretable. Second, we present methods that allow researchers to test causal claims in situations where randomization is not possible or when causal interpretation is confounded, including fixed-effects panel, sample selection, instrumental variable, regression discontinuity, and difference-in-differences models. Third, we take stock of the methodological rigor with which causal claims are being made in a social sciences discipline by reviewing a representative sample of 110 articles on leadership published in the previous 10 years in top-tier journals. Our key finding is that researchers fail to address at least 66 % and up to 90 % of design and estimation conditions that make causal claims invalid. We conclude by offering 10 suggestions on how to improve non-experimental research.

A comparison of three methods of Mendelian randomization when the genetic instrument, the risk factor and the outcome are all binary.

The method of instrumental variable (referred to as Mendelian randomization when the instrument is a genetic variant) has been initially developed to infer on a causal effect of a risk factor on some outcome of interest in a linear model. Adapting this method to nonlinear models, however, is known to be problematic. In this paper, we consider the simple case when the genetic instrument, the risk factor, and the outcome are all binary. We compare via simulations the usual two-stages estimate of a causal odds-ratio and its adjusted version with a recently proposed estimate in the context of a clinical trial with noncompliance. In contrast to the former two, we confirm that the latter is (under some conditions) a valid estimate of a causal odds-ratio defined in the subpopulation of compliers, and we propose its use in the context of Mendelian randomization. By analogy with a clinical trial with noncompliance, compliers are those individuals for whom the presence/absence of the risk factor X is determined by the presence/absence of the genetic variant Z (i.e., for whom we would observe X = Z whatever the alleles randomly received at conception). We also recall and illustrate the huge variability of instrumental variable estimates when the instrument is weak (i.e., with a low percentage of compliers, as is typically the case with genetic instruments for which this proportion is frequently smaller than 10%) where the inter-quartile range of our simulated estimates was up to 18 times higher compared to a conventional (e.g., intention-to-treat) approach. We thus conclude that the need to find stronger instruments is probably as important as the need to develop a methodology allowing to consistently estimate a causal odds-ratio.

Relationship between obesity and the risk of clinically significant depression: Mendelian randomisation study.

BACKGROUND: Obesity has been shown to be associated with depression and it has been suggested that higher body mass index (BMI) increases the risk of depression and other common mental disorders. However, the causal relationship remains unclear and Mendelian randomisation, a form of instrumental variable analysis, has recently been employed to attempt to resolve this issue. AIMS: To investigate whether higher BMI increases the risk of major depression. METHOD: Two instrumental variable analyses were conducted to test the causal relationship between obesity and major depression in RADIANT, a large case-control study of major depression. We used a single nucleotide polymorphism (SNP) in FTO and a genetic risk score (GRS) based on 32 SNPs with well-established associations with BMI. RESULTS: Linear regression analysis, as expected, showed that individuals carrying more risk alleles of FTO or having higher score of GRS had a higher BMI. Probit regression suggested that higher BMI is associated with increased risk of major depression. However, our two instrumental variable analyses did not support a causal relationship between higher BMI and major depression (FTO genotype: coefficient -0.03, 95% CI -0.18 to 0.13, P = 0.73; GRS: coefficient -0.02, 95% CI -0.11 to 0.07, P = 0.62). CONCLUSIONS: Our instrumental variable analyses did not support a causal relationship between higher BMI and major depression. The positive associations of higher BMI with major depression in probit regression analyses might be explained by reverse causality and/or residual confounding.

Testing mediation: The endogeneity problem and the solution

A mediator is a dependent variable, m (e.g., charisma), that is thought to channel the effect of an independent variable, x (e.g., receiving training or not), on another dependent variable (e.g., subordinate satisfaction), y. In experimental settings x is manipulated-subjects are randomized to treatment-to isolate the causal effect of x on other variables. If m is not or cannot be manipulated, which is often the case, its causal effect on other variables cannot be determined; thus, standard mediation tests cannot inform policy or practice. I will show how an econometric procedure, called instrumental-variable estimation, can examine mediation in such cases.

Variable viral clearance despite adequate ganciclovir plasma levels during valganciclovir treatment for cytomegalovirus disease in D+/R- transplant recipients.

ABSTRACT: BACKGROUND: Valganciclovir, the oral prodrug of ganciclovir, has been demonstrated equivalent to iv ganciclovir for CMV disease treatment in solid organ transplant recipients. Variability in ganciclovir exposure achieved with valganciclovir could be implicated as a contributing factor for explaining variations in the therapeutic response. This prospective observational study aimed to correlate clinical and cytomegalovirus (CMV) viral load response (DNAemia) with ganciclovir plasma concentrations in patients treated with valganciclovir for CMV infection/disease. METHODS: Seven CMV D+/R- transplant recipients (4 kidney, 2 liver and 1 heart) were treated with valganciclovir (initial dose was 900-1800 mg/day for 3-6.5 weeks, followed by 450-900 mg/day for 2-9 weeks). DNAemia was monitored by real time quantitative PCR and ganciclovir plasma concentration was measured at trough (Ctrough) and 3 h after drug administration (C3h) by HPLC. RESULTS: Four patients presented with CMV syndrome, two had CMV tissue-invasive disease after prophylaxis discontinuation, and one liver recipient was treated pre-emptively for asymptomatic rising CMV viral load 5 weeks post-transplantation in the absence of prophylaxis. CMV DNAemia decreased during the first week of treatment in all recipients except in one patient (median decrease: -1.2 log copies/mL, range: -1.8 to 0) despite satisfactory ganciclovir exposure (AUC0-12 = 48 mg.h/L, range for the 7 patients: 40-118 mg.h/L). Viral clearance was obtained in five patients after a median of time of 34 days (range: 28-82 days). Two patients had recurrent CMV disease despite adequate ganciclovir exposure (65 mg.h/L, range: 44-118 mg.h/L). CONCLUSIONS: Valganciclovir treatment for CMV infection/disease in D+/R- transplant recipients can thus result in variable viral clearance despite adequate ganciclovir plasma concentrations, probably correlating inversely with anti-CMV immune responses after primary infection.

Variable phenotypic expressivity in a Swiss family with autosomal dominant retinitis pigmentosa due to mutation T494m in the Prpf3 gene

Purpose:to describe the clinical features in a five generations family segregating autosomal dominant retinitis pigmentosa and to identify the causative gene Patient and Methods:Twenty five individuals of a large five-generation family originating from Western Switzerland were ascertained for phenotypic and genotypic characterization. Ophthalmologic evaluations included color vision testing, Goldman perimetry and digital fundus photography. Some patients had autofluorescence (AF) imaging, ocular coherence tomography (OCT) and ISCEV-standard full-field electroretinography (ERG). Blood samples were collected from 10 affected (4 to 70 years of age) and 15 unaffected members after informed consent. DNA was isolated and exons and intron-exons junctions of known adRP genes were sequenced using a Big Dye sequencing kit 1.1. Results:Age of onset of nightblindness and severity of progression of the disease was variable between members of the family. Some patients had early onset of nightblindess aged 3, others at mid-twenties. Most patients had visual acuity above 0.6 for the first 4 decades. Two older patients still had good vision (0.4) in their seventies. Myopia (range: -2 to -5) was noticed in most affected subjects. Fundus findings showed areas of atrophy along the arcades. The AF imaging showed a large high density ring bilaterally. A T494M change was found in exon 11 of PRPF3 gene. The change segregates with the disease in the family. Conclusion: A mutation in the PRPF3 gene is rare compared with other genes causing ADRP. Although a T494M change has been reported, our family is the first one with a variable expressivity. Mutations in PRPF3 gene can cause a variable phenotype of ADRP unlike the previously described Danish and English families. Our report gives a better understanding as to the phenotype/genotype description of ADRP due to PRPF3 mutation.

Two monoclonal rat antibodies with specificity for the beta-chain variable region V beta 6 of the murine T-cell receptor.

Two rat monoclonal antibodies (mAbs), 44-22-1 and 46-6B5, which recognize an alloreactive cytotoxic clone, 3F9, have been further tested on a panel of T hybridomas and cytotoxic T-cell clones for binding and functional activities. The mAbs recognized only those cells sharing the expression of the T-cell receptor beta-chain variable region gene V beta 6 with 3F9. All V beta 6+ cells were activated by these mAbs under cross-linking conditions and their antigen-specific activation was blocked by soluble mAb. Furthermore, depletion of 46-6B5+ normal lymph node T cells eliminated all cells expressing the epitope recognized by 44-22-1 and V beta 6 mRNA.

Immunodéficience commune variable: ce qu'il faut savoir [Common variable immune deficiency: what you need to know].

Common variable immune deficiency is the most frequent primary immune deficiency, characterized mainly by a disorder of B lymphocytes differentiation and a deficit in immunoglobulins. The clinical manifestations include recurrent infections, non-infectious lung and digestive involvements, autoimmune diseases, and an increased susceptibility to cancers. Recent breakthroughs have been made in the understanding of some genetic mechanisms of the disease. Replacement therapy with intravenous immunoglobulins remains the treatment of choice, which allows significant improvement in the survival and quality of life. However progress should be made in the understanding of the pathophysiology and in the early detection of this disease, since a delay in the diagnosis may have harmful consequences in terms of morbidity and mortality.

Assessing the Relationship between the Baseline Value of a Continuous Variable and Subsequent Change over Time

Analyzing the relationship between the baseline value and subsequent change of a continuous variable is a frequent matter of inquiry in cohort studies. These analyses are surprisingly complex, particularly if only two waves of data are available. It is unclear for non-biostatisticians where the complexity of this analysis lies and which statistical method is adequate.With the help of simulated longitudinal data of body mass index in children,we review statistical methods for the analysis of the association between the baseline value and subsequent change, assuming linear growth with time. Key issues in such analyses are mathematical coupling, measurement error, variability of change between individuals, and regression to the mean. Ideally, it is better to rely on multiple repeated measurements at different times and a linear random effects model is a standard approach if more than two waves of data are available. If only two waves of data are available, our simulations show that Blomqvist's method - which consists in adjusting for measurement error variance the estimated regression coefficient of observed change on baseline value - provides accurate estimates. The adequacy of the methods to assess the relationship between the baseline value and subsequent change depends on the number of data waves, the availability of information on measurement error, and the variability of change between individuals.

Instrumental leadership: Measurement and extension of transformational-transactional leadership theory.

Leaders must scan the internal and external environment, chart strategic and task objectives, and provide performance feedback. These instrumental leadership (IL) functions go beyond the motivational and quid-pro quo leader behaviors that comprise the full-range-transformational, transactional, and laissez faire-leadership model. In four studies we examined the construct validity of IL. We found evidence for a four-factor IL model that was highly prototypical of good leadership. IL predicted top-level leader emergence controlling for the full-range factors, initiating structure, and consideration. It also explained unique variance in outcomes beyond the full-range factors; the effects of transformational leadership were vastly overstated when IL was omitted from the model. We discuss the importance of a "fuller full-range" leadership theory for theory and practice. We also showcase our methodological contributions regarding corrections for common method variance (i.e., endogeneity) bias using two-stage least squares (2SLS) regression and Monte Carlo split-sample designs.

Characteristics of eyes with secondary loss of visual acuity receiving variable dosing ranibizumab for neovascular age-related macular degeneration.

PURPOSE: The aim of this work is to investigate the characteristics of eyes failing to maintain visual acuity (VA) receiving variable dosing ranibizumab for neovascular age-related macular degeneration (nAMD) after three initial loading doses. METHODS: A consecutive series of patients with nAMD, who, after three loading doses of intravitreal ranibizumab (0.5 mg each), were re-treated for fluid seen on optical coherence tomography. After exclusion of eyes with previous treatment, follow-up less than 12 months, or missed visits, 99 patients were included in the analysis. The influence of baseline characteristics, initial VA response, and central retinal thickness (CRT) fluctuations on the VA stability from month 3 to month 24 were analyzed using subgroups and multiple regression analyses. RESULTS: Mean follow-up duration was 21.3 months (range 12-40 months, 32 patients followed-up for ≥24 months). Secondary loss of VA (loss of five letters or more) after month 3 was seen in 30 patients (mean VA improvement from baseline +5.8 letters at month 3, mean loss from baseline -5.3 letters at month 12 and -9.7 at final visit up to month 24), while 69 patients maintained vision (mean gain +8.9 letters at month 3, +10.4 letters at month 12, and +12.8 letters at final visit up to month 24). Secondary loss of VA was associated with the presence of pigment epithelial detachment (PED) at baseline (p 0.01), but not with baseline fibrosis/atrophy/hemorrhage, CRT fluctuations, or initial VA response. Chart analysis revealed additional individual explanations for the secondary loss of VA, including retinal pigment epithelial tears, progressive fibrosis, and atrophy. CONCLUSIONS: Tissue damage due to degeneration of PED, retinal pigment epithelial tears, progressive fibrosis, progressive atrophy, or massive hemorrhage, appears to be relevant in causing secondary loss of VA despite vascular endothelial growth factor suppression. PED at baseline may represent a risk factor.