Partial possibilistic regression path modeling: handling uncertainty in path modeling
نویسندگان
چکیده
منابع مشابه
Consistent Partial Least Squares Path Modeling
This paper resumes the discussion in information systems research on the use of partial least squares (PLS) path modeling and shows that the inconsistency of PLS path coefficient estimates in the case of reflective measurement can have adverse consequences for hypothesis testing. To remedy this, the study introduces a vital extension of PLS: consistent PLS (PLSc). PLSc provides a correction for...
متن کاملReflections on Partial Least Squares Path Modeling
The purpose of the present article is to take stock of a recent exchange in Organizational Research Methods between critics and proponents of partial least squares path modeling (PLS-PM). The two target articles were centered around six principal issues, namely whether PLS-PM: (a) can be truly characterized as a technique for structural equation modeling (SEM), (b) is able to correct for measur...
متن کاملHow to Address Endogeneity in Partial Least Squares Path Modeling
Some of the models using partial least squares (PLS) in Information Systems (IS) field may have serious problems because do not properly address endogeneity. This may suppose a problem in IS theory building because it may lead IS scholars to non-correct results. Although the IS community’s awareness is rising, we do not have a clear understanding of the problem nor fine-grained practical guidel...
متن کاملPredictive model selection in partial least squares path modeling
Predictive model selection metrics are used to select models with the highest out-of-sample predictive power among a set of models. R 2 and related metrics, which are heavily used in partial least squares path modeling, are often mistaken as predictive metrics. We introduce information theoretic model selection criteria that are designed for out-of-sample prediction and which do not require cre...
متن کاملConstruct Validity in Partial Least Squares Path Modeling
Partial least squares path modeling (PLS) has seen increased use in the information systems research community. One of the stated key advantages of PLS is that it weights the indicator variables based on the strength of the relationship between the indicators and the underlying constructs, which presumably decreases the effect of measurement error in the analysis results. In this paper we argue...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computational Statistics
سال: 2020
ISSN: 0943-4062,1613-9658
DOI: 10.1007/s00180-020-01026-7