Linked Questions
58 questions linked to/from Interpretation of simple predictions to odds ratios in logistic regression
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interpreting logistic regression output: how to relate predicted values to coefficients [duplicate]
I see many questions on this topic, but I promise none seem to explain what I'm after.
I want to understand how to tie the coefficients I get from a logistic regression model back to the model ...
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What is the difference between logistic and logit regression?
What is the difference between logistic and logit regression? I understand that they are similar (or even the same thing) but could someone explain the difference(s) between these two? Is one about ...
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Pooling data for logistic regression
I want to run a logistic regression on greyhound races. For each race I have a dummy variable (y) that takes value one when the dog wins and zero otherwise.
Unfortunately the number of hounds in each ...
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Odds ratio from logistic regression isn't negative when it should be
I just recently started working with logistic regression, and I'm struggling with the interpretation of the results.
Say I have brain disease (BD) as an outcome and gestational age (GE) as an ...
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Understanding the intercept in an unadjusted logistic regression
I have performed an unadjusted logistic regression using weights (obtained via genetic matching) as below. I am using the survey package to make working with the ...
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What is the intuition behind the odds scale?
What is an intuitive explanation of the odds scale?
In a logistic regression such as $$logit(p) = \beta_0 + \beta_1 x$$
we often interpret $\beta_1$ by looking at the odds ratio, $e^{\beta_1}$, which ...
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Understanding binary logistic regression as a linear model
I understand that binary logistic regression is applied to binary classification problems where the dependent variable $Y$ has only two possible outcomes. The independent variables are $x$. The result ...
391
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Difference between logit and probit models
What is the difference between Logit and Probit model?
I'm more interested here in knowing when to use logistic regression, and when to use Probit.
If there is any literature which defines it using ...
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Meaning of an odds ratio in mixed effects logistic regression
Pardon my ignorance but I am looking for some statistics help. I ran a mixed effects logistic regression and produced a summary table in R. Because of the nature of the regression type I don't have ...
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What does the logit value actually mean?
I have a logit model that comes up with a number between 0 and 1 for many cases, but how can we interprete this?
Lets take a case with a logit of 0.20
Can we assert that there is 20% probability ...
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Interpreting logistic regression coefficients for a categorical variable
I got these results from a logistic regression in R. The data are the proportion of women elected in Uk elections, according to their party.
As you can see, I used ...
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RMSE (Root Mean Squared Error) for logistic models
I have a question regarding the validity of using RMSE (Root Mean Squared Error) to compare different logistic models. The response is either 0 or ...
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Simulating a logistic regression in R
I'm trying to simulate data for a logistic regression experiment to predict $50$ students pass/fail outcome on a math course from their GRE quant. scores.
GRE quant. is known to be normally ...
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What is an intuitive interpretation of the leaf values in XGBoost base learners?
I'm learning XGBoost. The following is the code I used and below that is the tree #0 and #1 in the XGBoost model I built.
I'm having a hard time understanding the meanings of the leaf values. Some ...
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Odds Ratio vs. Probability? [duplicate]
I have a question about odds ratios vs. probabilities in terms of a contingency table (studying an exposure/disease). I know that once I have found an odds ratio, I can also find the probability by ...