Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Reconciling design-based and model-based causal inferences for
  split-plot experiments   The split-plot design assigns different interventions at the whole-plot and
sub-plot levels, respectively, and induces a group structure on the final
treatment assignments. A common strategy is to use the OLS fit of the outcome
on the treatment indicators coupled with the robust standard errors clustered
at the whole-plot level. It does not give consistent estimator for the causal
effects of interest when the whole-plot sizes vary. Another common strategy is
to fit the linear mixed-effects model of the outcome with Normal random effects
and errors. It is a purely model-based approach and can be sensitive to
violations of parametric assumptions. In contrast, the design-based inference
assumes no outcome models and relies solely on the controllable randomization
mechanism determined by the physical experiment. We first extend the existing
design-based inference based on the {\htf} estimator to the Hajek estimator,
and establish the finite-population central limit theorem for both under
split-plot randomization. We then reconcile the results with those under the
model-based approach, and propose two regression strategies, namely (i) the WLS
fit of the unit-level data based on the inverse probability weighting and (ii)
the OLS fit of the aggregate data based on whole-plot total outcomes, to
reproduce the Hajek and {\htf} estimators from least squares, respectively.
This, together with the asymptotic conservativeness of the corresponding
cluster-robust covariances for estimating the true design-based covariances as
we establish in the process, justifies the validity of regression-based
estimators for design-based inference. In light of the flexibility of
regression formulation with covariate adjustment, we further extend the theory
to the case with covariates and demonstrate the efficiency gain by
regression-based covariate adjustment via both asymptotic theory and
simulation.

27
The categories of this paper are: comp-gas
7
The categories of this paper are: hep-th
3
The categories of this paper are: physics
32
The categories of this paper are: atom-ph
24
The categories of this paper are: dg-ga
25
The categories of this paper are: patt-sol
21
The categories of this paper are: adap-org
15
The categories of this paper are: nucl-ex
0
The categories of this paper are: hep-ph
19
The categories of this paper are: eess
8
The categories of this paper are: hep-ex
20
The categories of this paper are: acc-phys
17
The categories of this paper are: q-fin
10
The categories of this paper are: q-bio
28
The categories of this paper are: alg-geom
30
The categories of this paper are: q-alg