Questions tagged [partial-effect]
The partial effect of individual explanatory/predictor variables from a fitted model on a dependent variable.
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Why are these Partial Residual Plots similar despite having different y-axis (partial residual range vs. component + residual)
I am working to produce some partial residual plots to better communicates the effects associated with each independent variable in a multiple regression model. I am using two methods to plot these ...
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Partial eta square values summing to greater than 1
I am trying to run a factorial ANOVA analysis with partial effects, but it seems that my partial eta square values are totalling above 1, particularly when I specify my contrast with Type II or Type ...
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Variance partitioning when using a response from 1st study as a predictor in 2nd study
I use linear mixed-effects models to analyze my data, where I have a variable C that is used as a response and an explanatory variable in separate studies.
In the first study C ~ A + (1|B),
I found ...
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Should individual $R^2$ of a predictor always be greater than $\Delta R^2$ when removing that predictor from an expanded model?
I'm running some regressions with a set of somewhat correlated predictors. Let's call these predictors $x$, $y$ and $z$, and my dependent variable $d$.
I'm focused on the effect of $x$ on $d$.
I first ...
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Creating a partial dependant plot for a prediction function [closed]
I am working on creating a partial dependant plot for one of my features (B). The problem is that I didn't use any model to predict my output (R). I've used a ...
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How to test if $x_1$ has a positive partial effect on $y$ taking into account the linear and quadratic components of $x_1$?
I have a quadratic population model of the form:
$y=\beta_0+\beta_1x_1+\beta_2x_2+\beta_3x_1^2+\mu$
I want to test if $x_1$ has a positive partial effect on $y$. How can I run such a hypothesis test ...
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GLM output says one thing, but glm graph says another, Simpson's Paradox?
I am running a GLM to evaluate the influence of canopy cover and vegetation density on average black-globe temperature. I ran a simple glm, but when I plot the model output, the plot does not agree ...
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Obtain Multiple Regression coefficients from Partial Correlation Coefficients and ANOVA table
I know, that results from multiple linear regression, partial correlation analysis and ANOVA are tightly related to each other.
The answers to this and this question indicate that the results may be &...
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Is the PARTIAL regression coefficient always smaller than the SIMPLE regression coefficient (when all variables are positively correlated)?
Suppose we have three variables: X1, X2, and Y. X1 and X2 are the independent variables (IVs) and Y is the dependent variable (DV). Suppose that each IV is positively associated with the DV. Suppose ...
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Can I partial out covariates with true coefficients known in Logit?
Suppose the model is
$$ \ln(\frac{P_{ij}}{1-P_{ij}}) = X_{ij}\beta_0 + A_i + A_j + \epsilon_{ij}, $$
The unit of observation is at $ij$ level, and $A_i$ and $A_j$ are coefficients on the dummy for ...
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How to test for a partially mediated model?
I have a dataset with three variables: Outcome, Exposure, and Mediator.
My hypothesis is that the variables are related as in the following DAG:
In particular I want to test that "Mediator" ...
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How to calculate percent partial deviance explained by each predictor variable in a GAM model?
I am trying to find a sensible way to calculate the deviance explained by each predictor variable in a GAM model and need some input on my calculations.
Following Simon Wood's example on the thread ...
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difference partial dependence and feature weights
Assume we train a linear model to predict a numeric outcome.
A feature's model weight would essentially quantify me how much the outcome variable increases for each increase in the predictor's value.
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Multicollinearity and Partial Dependence Questions
Assume I build a binary classification model to predict p(y=1) from {x1, x2, ... x10}
For now, assume that model could be a GBM, RandomForest, or Logistic Regression.
Also assume that all of the ...
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Partial and Semi-partial/Part correlation in matrix/vector form
For three variables, e.g. $X$, $Y$, and $Z$, it is easy for me to deduce the partial and semi-partial correlation coefficients (in general), however I cannot do the same for more than three variables. ...
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