Search Results - subject:"causal inference."

How Generalizable Is Your Experiment? An Index for Comparing Experimental Samples and Populations

Tipton, Elizabeth - In: Journal of Educational and Behavioral Statistics 39 (2014) 6, pp. 478-501

Although a large-scale experiment can provide an estimate of the average causal impact for a program, the sample of sites included in the experiment is often not drawn randomly from the inference population of interest. In this article, we provide a generalizability index that can be used to...

Persistent link: https://www.econbiz.de/10011099952

Comparative Hypothesis Testing Via Process Tracing

Rohlfing, Ingo - In: Sociological Methods & Research 43 (2014) 4, pp. 606-642

Causal inference via process tracing has received increasing attention during recent years. A 2 × 2 typology of … hypothesis tests takes a central place in this debate. A discussion of the typology demonstrates that its role for causal … inference can be improved further in three respects. First, the aim of this article is to formulate case selection principles …

Persistent link: https://www.econbiz.de/10011166233

Effects of Causes and Causes of Effects

Smith, Herbert L. - In: Sociological Methods & Research 43 (2014) 3, pp. 406-415

Sociology is pluralist in subject matter, theory, and method, and thus a good place to entertain ideas about causation associated with their use under the law. I focus on two themes: (1) the legal lens on causation that â€œconsiders populations in order to make statements about...

Persistent link: https://www.econbiz.de/10010892934

Optimal personalized treatment rules for marketing interventions: A review of methods, a new proposal, and an insurance case study

Guelman, Leo; Guillen, Montserrat; Pérez-Marín, Ana M. - Institut de Recerca en Economia Aplicada (IREA), … - 2014

In many important settings, subjects can show signicant heterogeneity in response to a stimulus or treatment". For instance, a treatment that works for the overall population might be highly ineective, or even harmful, for a subgroup of subjects with specic characteristics. Similarly, a new...

Persistent link: https://www.econbiz.de/10010908099

The effect of the prior distribution in the Bayesian Adjustment for Confounding algorithm

Lefebvre, Geneviève; Atherton, Juli; Talbot, Denis - In: Computational Statistics & Data Analysis 70 (2014) C, pp. 227-240

The effect of the prior distribution of the outcome and exposure models’ covariate inclusion indicators in the Bayesian Adjustment for Confounding (BAC) algorithm is studied. The investigative approach is to analytically describe the posterior probabilities of the outcome models in terms of...

Persistent link: https://www.econbiz.de/10011056562

Mendelian randomization in health research: Using appropriate genetic variants and avoiding biased estimates

Taylor, Amy E.; Davies, Neil M.; Ware, Jennifer J.; … - In: Economics & Human Biology 13 (2014) C, pp. 99-106

Mendelian randomization methods, which use genetic variants as instrumental variables for exposures of interest to overcome problems of confounding and reverse causality, are becoming widespread for assessing causal relationships in epidemiological studies. The main purpose of this paper is to...

Persistent link: https://www.econbiz.de/10011056645

The effect of school district nutrition policies on dietary intake and overweight: A synthetic control approach

Bauhoff, Sebastian - In: Economics & Human Biology 12 (2014) C, pp. 45-55

School nutrition policies aim to eliminate ubiquitous unhealthy foods and beverages from schools to improve adolescent dietary behavior and reduce childhood obesity. This paper evaluates the impact of an early nutrition policy, Los Angeles Unified School District's food-and-beverage standards of...

Persistent link: https://www.econbiz.de/10011056659

Estimation of causal effects in observational studies with interference between units

Lundin, Mathias; Karlsson, Maria - In: Statistical Methods and Applications 23 (2014) 3, pp. 417-433

Causal effects are usually estimated under the assumption of no interference between individuals. This assumption means that the potential outcomes for one individual are unaffected by the treatments received by other individuals. In many situations, this is not reasonable to assume. Moreover,...

Persistent link: https://www.econbiz.de/10010998672

Targeted smoothing parameter selection for estimating average causal effects

Häggström, Jenny; Luna, Xavier - In: Computational Statistics 29 (2014) 6, pp. 1727-1748

The non-parametric estimation of average causal effects in observational studies often relies on controlling for confounding covariates through smoothing regression methods such as kernel, splines or local polynomial regression. Such regression methods are tuned via smoothing parameters which...

Persistent link: https://www.econbiz.de/10011151863

The performance of non-experimental designs in the evaluation of environmental programs: A design-replication study using a large-scale randomized experiment as a benchmark

Ferraro, Paul J.; Miranda, Juan José - In: Journal of Economic Behavior & Organization 107 (2014) PA, pp. 344-365

In the field of environmental policy, randomized evaluation designs are rare. Thus researchers typically rely on observational designs to evaluate program impacts. To assess the ability of observational designs to replicate the results of experimental designs, researchers use design-replication...

Persistent link: https://www.econbiz.de/10011077026