Results 1 to 10 of about 15,773 (265)

Assessing the impact of variance heterogeneity and misspecification in mixed-effects location-scale models [PDF]

BMC Medical Research Methodology
Purpose Linear Mixed Model (LMM) is a common statistical approach to model the relation between exposure and outcome while capturing individual variability through random effects.
Vincent Jeanselme, Marco Palma, Jessica Barrett   +2 more
doaj   +2 more sources

Identifying the sources of model misspecification [PDF]

Journal of Monetary Economics, 2020
The first and third authors acknowledge financial support from the National Science Foundation through grants 102159 and 1022125, respectively.
Atsushi Inoue, Chun-Hung Kuo, Barbara Rossi   +2 more
exaly   +8 more sources

Generalized Information Matrix Tests for Detecting Model Misspecification

Econometrics, 2016
Generalized Information Matrix Tests (GIMTs) have recently been used for detecting the presence of misspecification in regression models in both randomized controlled trials and observational studies.
Richard M Golden, Halbert White
exaly   +3 more sources

Multicollinearity and Model Misspecification

Sociological Science, 2016
Multicollinearity in linear regression is typically thought of as a problem of large standard errors due to near-linear dependencies among independent variables. This problem can be solved by more informative data, possibly in the form of a larger sample.
Christopher Winship, Bruce Western
doaj   +3 more sources

In models we trust: preregistration, large samples, and replication may not suffice

Frontiers in Psychology, 2023
Despite discussions about the replicability of findings in psychological research, two issues have been largely ignored: selection mechanisms and model assumptions.
Martin Spiess, Pascal Jordan
doaj   +1 more source

Optimal weighting for estimating generalized average treatment effects

Journal of Causal Inference, 2022
In causal inference, a variety of causal effect estimands have been studied, including the sample, uncensored, target, conditional, optimal subpopulation, and optimal weighted average treatment effects.
Kallus Nathan, Santacatterina Michele
doaj   +1 more source

Model Misspecification as the Causes of Flypaper Effect

Proceedings, 2023
The aim of this paper is to investigate the relationship between the Fly-paper effect (FPE) and possible errors in the specification of econometric models used in the empirical analysis of FPE.
Siniša Mali
doaj   +1 more source

Effect of Probability Distribution of the Response Variable in Optimal Experimental Design with Applications in Medicine

Mathematics, 2021
In optimal experimental design theory it is usually assumed that the response variable follows a normal distribution with constant variance. However, some works assume other probability distributions based on additional information or practitioner’s ...
Sergio Pozuelo-Campos, Víctor Casero-Alonso, Mariano Amo-Salas   +2 more
doaj   +1 more source

Making Decisions under Model Misspecification [PDF]

SSRN Electronic Journal, 2020
Abstract We use decision theory to confront uncertainty that is sufficiently broad to incorporate “models as approximations.” We presume the existence of a featured collection of what we call “structured models” that have explicit substantive motivations.
Cerreia–Vioglio, Simone, Hansen, Lars Peter, Maccheroni, Fabio, Marinacci, Massimo   +3 more
openaire   +2 more sources

Estimation Methods of the Multiple-Group One-Dimensional Factor Model: Implied Identification Constraints in the Violation of Measurement Invariance

Axioms, 2022
Factor analysis is one of the most important statistical tools for analyzing multivariate data (i.e., items) in the social sciences. An essential case is the comparison of multiple groups on a one-dimensional factor variable that can be interpreted as a ...
Alexander Robitzsch
doaj   +1 more source