Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

Questions tagged [main-effects]

13 questions
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Why are Simple Effects only used when the interaction is significant?

I have conducted a 2-way ANOVA and obtained a significant Main Effect in IV1 and IV2, but a non-significant interaction. Following that, I have analyzed IV1 using a test for Simple Effects and received a significant Simple effect at level 1 and a…
Hecealdor
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lmer Dropping levels from summary information in models with main effect and interactions

First off, here are my models: lm1 <- lmer(log(y) ~ x1 + x2 + x3 + x4 + x5 + x6 + x7 + x8 + x9 + (1|x10/x11), data=df, na.action=na.exclude) lm2 <- lmer(log(y) ~ x1 + x2 + x3 + x4 + x5 + x6 + x7 + x8 + x9 + x12 + (1|x10/x11), data=df,…
UnsoughtNine
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Interpreting growth curve analysis (GCA) main effect in light of interaction (eye tracking data)

I have fit parabolas to two groups in a growth curve analysis (GCA) of eye tracking data using orthogonal polynomials (essentially by following Dan Mirman's example for his paper with Magnuson in 2009, Dynamics of activation of semantically similar…
Meg
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Main effect vs simple effect

In the following linear model: $y = \beta_0 +\beta_1 x_1 +\beta_2 x_2 + \beta_3x_1x_2 + \epsilon$ what are called $x_i$? The term $x_1x_2$ is the interaction. In ANOVA, $x_i$ are named "main effects", but in regression I saw a paper mentioning that…
POC
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Interaction effect in logistic regression

I have applied logit model, where my dependent variable is Emp (Employment) 1 if employed otherwise 0, and used level of education and Health status as independent variables where: Education consist 6 categories i.e. 1=No Edu, 2= Primary or less…
Salim Khan
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Why type III sum of squares is not recommended to use when there is significant interaction?

I did notice that in the following example, I obtained a insignificant main effect for treatment when including interaction, although the treatment is clearly effective. Any intuitive explanation? with interaction in the model: Source DF Type III SS…
hehe
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Factor Levels in a Two-Way ANOVA

I'm trying to figure out the explanations of the Effect Plots below. I believe I have figures out Figure 9a, but the explanation for Figures b, c, and d given in the textbook I do not comprehend. Any further detail would be greatly…
Chesso
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Given a specific model how would you find the possible effects and interactions of the factors?

I am looking for contaminations on two different beaches N and S at two different times T1 and T2. Where it is suggested that Beach N has a higher risk of contamination than beach S and the levels vary according to the different times. I have to…
Neha
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Is a "deviance table" equivalent to the type 2 or type 3 ANOVA?

I was taught, that ANOVA assesses the main effects and interaction effects of a linear model. In other words, it jointly tests appropriate model (with categorical IVs) parameters, telling us, if all the levels of the categorical IV jointly reduce…
OverTheRainbow
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Using Orthogonal Main Effects Plan to select profiles for conjoint analysis

I am trying to create a code in Python to select orthogonal profiles given some attributes and levels. For eg: {'Pressure':[40,55,70,80,90], 'Temperature':[290, 320, 350], 'Flow rate':[0.2,0.4,0.5,0.6,0.7], 'Time':[5,11]} If I need to a conjoint…
DS_1
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Prediction of a null-effect in the interaction but a main effect of condition

Let's assume I have 2 groups of subjects (A, B) and I test these groups in a task where I measure reaction time (RT) in two conditions (C1, C2), which I will analyze with an Anova. Is it legit to hypothesize that RTs for C1 are slower than those of…
giorgio-p
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Three-way MANOVA Interpretation

I'm interpreting a three-way MANOVA as part of my research, and have come across an interpretation challenge, with three independent variables (Factor A, Factor B, and Factor C) and two dependent variables (Outcome 1, Outcome 2). My multivariate…
Neszka
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How to handle interaction in this longitudinal model?

Let's assume we have the following result of a longitudinal experiment, which evaluates the effect of a fertilizer over time. The dependent variable is about "poor condition". The higher value, the worse condition. So it's about improvement over…
GibbsSampler10
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