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I conducted a mixed linear logit model with the glmer function. Now I have the results and have no clue how to interpret them. 

Fixed effects:
                      Estimate      
(Intercept)             5.5433     
Condition              -0.8081     
Probability            -4.8688     
Condition:Probability   0.4881

Condition contains the two values -1 and 1. Probability contains all values between 0 and 1.

How can I interpret these values? How can I get the logits into a probability? For example: Condition is -1 and Probability is 1. What is the main effect for condition as a probability?

Can anyone help me?

Milo
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RockJan
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1 Answers1

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Ok, after some research if found out by myself how to interpret the data. (Btw the condition is binary coded)

Here is the answer:

First, you calculate the predicted value like this:

L = intercept + b1 * condition + b2*probability + b3*condition*probability. Then you can calculate the probabiliy: Pr(Y=1) = 1/(1+exp(-L))

For my example: Condition is -1 and Probability is 1. L= 5,54 + (-0.81*-1) + (-4.87*1) + (0.49*(-1)*1) = 0.99

Convert the Logit into Probability: Pr(Y=1) = 1/(1+exp(-0.99)) = 0.73

For condition -1 and probability 1 the calculatet probability is 73%

RockJan
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