In the recent comparative literature the problem of simultaneously modeling func-tional and diffusional effects is being penetrated from two directions. One approach emphasizes the similar problem which arises in regression-based time series analysis. A second approach focuses on the difficulties of constructing more realistic formal representations of sample unit interdependencies. Both approaches have yielded important and complementary, but distinct, insights. Here, we outline some recent methodological developments which synthesize both approaches into a comprehen-sive and unified analytical framework. 1.0 Introduction: Galton’s Problem as Spatial Autocorrelation The oldest fundamental criticism of cross-cultural research is that measur...
The effects of Galton's problem are discussed within a framework provided by the linear regression m...
Abstract. Dynamic models have been studied intensively during the last decade, particularly in the f...
We propose applying the multiparametric spatiotemporal autoregressive (m-STAR) model as a simple app...
In the recent comparative literature the problem of simultaneously modeling functional and diffusion...
Classical statistical inference procedures usually assume the independence of sample units. However,...
Classical statistical inference procedures usually assume the independence of sample units. However,...
Spatial interdependence, the interdependence of outcomes across units, is theoretically and substant...
ABSTRACT: Spatial interdependence, the interdependence of outcomes across units, is theoretically an...
Spatial interdependence–the dependence of outcomes in some units on those in others–is substantively...
Dow and Eff recently reported high levels of network autocorrelation for over eleven hundred and fif...
Spatial interdependence--the dependence of outcomes in some units on those in others--is substantive...
Positive autocorrelation implies that proximate observations take on similar values. “Proximate” can...
Psychological research increasingly focuses on how processes interact over time at the within-person...
Positive autocorrelation implies that proximate observations take on similar values. “Proximate ” ca...
Spatial interdependence-the dependence of outcomes in some units on those in others-is substantively...
The effects of Galton's problem are discussed within a framework provided by the linear regression m...
Abstract. Dynamic models have been studied intensively during the last decade, particularly in the f...
We propose applying the multiparametric spatiotemporal autoregressive (m-STAR) model as a simple app...
In the recent comparative literature the problem of simultaneously modeling functional and diffusion...
Classical statistical inference procedures usually assume the independence of sample units. However,...
Classical statistical inference procedures usually assume the independence of sample units. However,...
Spatial interdependence, the interdependence of outcomes across units, is theoretically and substant...
ABSTRACT: Spatial interdependence, the interdependence of outcomes across units, is theoretically an...
Spatial interdependence–the dependence of outcomes in some units on those in others–is substantively...
Dow and Eff recently reported high levels of network autocorrelation for over eleven hundred and fif...
Spatial interdependence--the dependence of outcomes in some units on those in others--is substantive...
Positive autocorrelation implies that proximate observations take on similar values. “Proximate” can...
Psychological research increasingly focuses on how processes interact over time at the within-person...
Positive autocorrelation implies that proximate observations take on similar values. “Proximate ” ca...
Spatial interdependence-the dependence of outcomes in some units on those in others-is substantively...
The effects of Galton's problem are discussed within a framework provided by the linear regression m...
Abstract. Dynamic models have been studied intensively during the last decade, particularly in the f...
We propose applying the multiparametric spatiotemporal autoregressive (m-STAR) model as a simple app...