# Questions tagged [regression]

Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

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### Plotting predicted common OR and 95% CI from an ordinal logistic regression model

I fitted an ordinal logistic regression model with a dependent variable of four ordered responses with one continuous predictor variable and 6 confounders, using the polr package in R. It looks like ...
1answer
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### Is the sum of 3 bits a linearly separable task?

In other words can a linear classifier learn to correctly assign a class (label 0 to 3) for an input of 3 bits? Intuitively this cannot work, since the half-adder circuit contains an XOR block, which ...
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### How regression coefficients change when shifting the scale of the response variable

I am running a regression with y: a 7 point index ranging from -3 to 3, x: binary indicator (0,1) of second wave of data collection. When I fit this regression, I get the following equation: ...
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### What is the sampling distributions underlying a moderated (interaction) effect?

I'm trying to derive the underlying sampling distribution of moderated effects (product of two continuous random variables), to compute its statistical power. At this point, I'm mostly interested in ...
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### Centering continuous variables in a multilevel logistic regression model

We are fitting a two-level logistic regression model with continuous variables in Level 1 and no variables in Level 2, except the groups. We considered only a random intercept in the model, but it is ...
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### Why I get same predictions values for diferent input data?

I am newbie in the neural network world and actually I build my first neural network but for some reason when I use de trained model to predict ,giving by myselft the data I want it to predict it, ...
1answer
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### Can I use linear regression when one group has positive correlation and another negative of X with Y?

I am wondering if I can use regression of the type Y=a+b1X1D1+b2X2D1+b3X3D1+... As a result, I am planning to use dummy group variable for each of X's. The assumption of the linear regression tells ...