The Case-time-control Method for Nonbinary Exposures
Bibliographic Data
| ID | 6169893 |
|---|---|
| Authors | Arvid Sjölander (0000-0001-5226-6685, Karolinska Institutet, Stockholm, Sweden, corresponding author) |
| Year | 2017 |
| Volume | 47 |
| Issue | 1 |
| Pages | 182-211 |
| Publication date | 2017-03-27 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Sociological Methodology (JOURNAL) |
| Journal identifiers | ISSN: 0081-1750 • E-ISSN: 1467-9531 |
| Publisher | SAGE Publishing (PUBLISHER • US) |
| DOI | 10.1177/0081175017692624 |
| OpenAlex | W2600524693 |
| Language | EN |
| Citations received | 1 |
| References cited | 20 |
A popular way to reduce confounding in observational studies is to use each study participant as his or her own control. This is possible when both the exposure and the outcome are time varying and have been measured at several time points for each individual. The case-time-control method is a special case, which, under certain assumptions, allows the analyst to control for confounding by time-varying covariates, while controlling for all time-stationary characteristics of the study participants. There are two formulations of the case-time-control method. One formulation requires that the exposure be binary, and the other requires that there be no more than two time points per individual. In this article the author proposes a generalization of the case-time-control method for nonbinary exposures and an arbitrary number of time points. The author derives the asymptotic properties of the resulting estimator and assesses its finite sample properties in a simulation study
Confounding · Control (management · Covariate · Econometrics · Estimator · Generalization · Mathematical economics · Observational study · Outcome (game theory · Sample (material · Statistics · Advanced Causal Inference Techniques · Artificial Intelligence · Computer Science · Mathematics · Statistical Methods and Inference · Statistical Methods in Clinical Trials
Causality
Fixed Effects Regression Models
Generalized Linear Models
The Case-Crossover Design
Estimating causal effects of treatments in randomized and nonrandomized studies.
Investigating the mechanism of marital mortality reduction
Fixed-Effects Methods for the Analysis of Nonrepeated Events
Long-term mortality consequences of childhood family context in Liaoning, China, 1749-1909
| Unique citing works | 1 |
|---|---|
| Citations per year | 0,14 |
| Citation span | 2019 - 2019 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 1 |