Interpreting spatial regression models with multiplicative interaction explanatory variables
نویسندگان
چکیده
Use of multiplicative interaction explanatory variables has been a standard practice in the regression modeling literature, and estimation parameters such model case spatial autoregressive (SAR) or Durbin (SDM) models can be accomplished using existing software for estimation. However, use conventional scalar summary estimates direct indirect effects reflecting own- other-region impacts on dependent variable associated with changes will not produce valid inferences. We discuss issues that arise introduce new methods interpretation based from this type model.
منابع مشابه
Linear regression with compositional explanatory variables
Compositional explanatory variables should not be directly used in a linear regression model because any inference statistic can become misleading. While various approaches for this problem were proposed, here an approach based on the isometric logratio (ilr) transformation is used. It turns out that the resulting model is easy to handle, and that parameter estimation can be done like in usual ...
متن کاملRegression Transformation Diagnostics for Explanatory Variables
Two types of diagnostics are presented for the transformation of explanatory variables in regression. One is based on the likelihood displacement proposed by Cook and Weisberg (1982) for assessing the in uence of individual cases on the maximum likelihood estimate of a transformation parameter. The other is based on the local in uence theory proposed by Cook (1986) for assessing the in uence of...
متن کاملInterpreting Complex Regression Models
Interpretation of a machine learning induced models is critical for feature engineering, debugging, and, arguably, compliance. Yet, best of breed machine learning models tend to be very complex. This paper presents a method for model interpretation which has the main benefit that the simple interpretations it provides are always grounded in actual sets of learning examples. The method is valida...
متن کاملA new method for dealing with measurement error in explanatory variables of regression models.
We introduce a new method, moment reconstruction, of correcting for measurement error in covariates in regression models. The central idea is similar to regression calibration in that the values of the covariates that are measured with error are replaced by "adjusted" values. In regression calibration the adjusted value is the expectation of the true value conditional on the measured value. In ...
متن کاملRegression Models with Ordinal Variables*
Most discussions of ordinal variables in the sociological literature debate the suitability of linear regression and structural equation methods when some variables are ordinal. Largely ignored in these discussions are methods for ordinal variables that are natural extensions of probit and logit models for dichotomous variables. If ordinal variables are discrete realizations of unmeasured conti...
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: Journal of Geographical Systems
سال: 2021
ISSN: ['1435-5930', '1435-5949']
DOI: https://doi.org/10.1007/s10109-021-00356-4