Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Within-Person Variability Score-Based Causal Inference: A Two-Step
  Estimation for Joint Effects of Time-Varying Treatments   Behavioral science researchers have shown strong interest in disaggregating
within-person relations from between-person differences (stable traits) using
longitudinal data. In this paper, we propose a method of within-person
variability score-based causal inference for estimating joint effects of
time-varying continuous treatments by effectively controlling for stable
traits. After explaining the assumed data-generating process and providing
formal definitions of stable trait factors, within-person variability scores,
and joint effects of time-varying treatments at the within-person level, we
introduce the proposed method, which consists of a two-step analysis.
Within-person variability scores for each person, which are disaggregated from
stable traits of that person, are first calculated using weights based on a
best linear correlation preserving predictor through structural equation
modeling (SEM). Causal parameters are then estimated via a potential outcome
approach, either marginal structural models (MSMs) or structural nested mean
models (SNMMs), using calculated within-person variability scores. Unlike the
approach that relies entirely on SEM, the present method does not assume
linearity for observed time-varying confounders at the within-person level. We
emphasize the use of SNMMs with G-estimation because of its property of being
doubly robust to model misspecifications in how observed time-varying
confounders are functionally related with treatments/predictors and outcomes at
the within-person level. Through simulation, we show that the proposed method
can recover causal parameters well and that causal estimates might be severely
biased if one does not properly account for stable traits. An empirical
application using data regarding sleep habits and mental health status from the
Tokyo Teen Cohort study is also provided.

29
The categories of this paper are: funct-an
11
The categories of this paper are: hep-lat
37
The categories of this paper are: supr-con
17
The categories of this paper are: q-fin
15
The categories of this paper are: nucl-ex
14
The categories of this paper are: math-ph
26
The categories of this paper are: bayes-an
13
The categories of this paper are: quant-ph
10
The categories of this paper are: q-bio
21
The categories of this paper are: adap-org
36
The categories of this paper are: cmp-lg
9
The categories of this paper are: nlin
19
The categories of this paper are: eess
0
The categories of this paper are: hep-ph
35
The categories of this paper are: mtrl-th
30
The categories of this paper are: q-alg