Further classification is made of Lindquist's dichotomy of inter action effects. The extension hopefully reduces errors of inter pretation and provides a simple, accurate means of summarizing in teractions obtained.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/67338/2/10.1177_001316448004000405.pd
<p>a) A symmetric interaction matrix and the corresponding correlation matrix. b) There is no relati...
A possible explanation of interaction is that quantities derived from the independent variables sepa...
Although interaction effects can be exploited to improve predictions and allow for valuable insights...
Authors often do not give sufficient information to draw conclu-sions about the size and statistical...
Identifying interactions and understanding the underlying generating mechanism is essential for inte...
Aptitude-treatment interaction (ATI) studies have been used with some frequency, yet many researcher...
Further classification is made of Lindquist’s dichotomy of inter-action effects. The extension hopef...
BACKGROUND: Directed acyclic graphs (DAGs) are of great help when researchers try to understand the ...
Re-parameterized regression models may enable tests of crucial theoretical predictions involving int...
In hierarchical data, the effect of a lower-level predictor on a lower-level outcome may often be co...
The paper compares Bales ’ Interaction Process Analysis (IPA) with Sacks ’ Conver-sation Analysis (C...
To make decisions, multiple data are used. It is preferred to decide on the basis of each datum sepa...
An interaction effect exists when the influence of an independent variable X on an outcome variable ...
The principle focus of this paper is on interpretation of interactions that are obtained when respon...
© Taylor & FrancisWhether or not there is an interaction between two factors in their effects on a d...
<p>a) A symmetric interaction matrix and the corresponding correlation matrix. b) There is no relati...
A possible explanation of interaction is that quantities derived from the independent variables sepa...
Although interaction effects can be exploited to improve predictions and allow for valuable insights...
Authors often do not give sufficient information to draw conclu-sions about the size and statistical...
Identifying interactions and understanding the underlying generating mechanism is essential for inte...
Aptitude-treatment interaction (ATI) studies have been used with some frequency, yet many researcher...
Further classification is made of Lindquist’s dichotomy of inter-action effects. The extension hopef...
BACKGROUND: Directed acyclic graphs (DAGs) are of great help when researchers try to understand the ...
Re-parameterized regression models may enable tests of crucial theoretical predictions involving int...
In hierarchical data, the effect of a lower-level predictor on a lower-level outcome may often be co...
The paper compares Bales ’ Interaction Process Analysis (IPA) with Sacks ’ Conver-sation Analysis (C...
To make decisions, multiple data are used. It is preferred to decide on the basis of each datum sepa...
An interaction effect exists when the influence of an independent variable X on an outcome variable ...
The principle focus of this paper is on interpretation of interactions that are obtained when respon...
© Taylor & FrancisWhether or not there is an interaction between two factors in their effects on a d...
<p>a) A symmetric interaction matrix and the corresponding correlation matrix. b) There is no relati...
A possible explanation of interaction is that quantities derived from the independent variables sepa...
Although interaction effects can be exploited to improve predictions and allow for valuable insights...
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