Questions tagged [logistic]
Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression
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how to improve logistic regression model in python
I have 1 million raw data points, and I dropped 2 independent variable because the have over 80% missing value.
All my variables are categorical except for "age" which I scaled between -1 ...
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Interpreting odds ratio greater than 2
Seems to be a lot of answers for interpreting odds ratios < 1 and > 1, but none for odds ratios > 2?
If I have an odds ratio of 2.22, does this mean there is a 122% increase in the odds for a ...
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Understanding feature significance in logistics regression [duplicate]
I have a classification problem. The response is whether a player will be banned (Yes=1 or No=0). I am considering a feature whether a player cheats. Intuitively, if a player cheats, they should be ...
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Logistic regression coefficients compared to the mean in R
No doubt this is a stupid question but I can't seem to find help anywhere online.
I want to do a logistic regression with 2 independent variables.
Ideally, I would like to see how each variable ...
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Logistic regression : contrast vs. changing reference group
I have a dataset with a dependent binary variable and one independent variable (with five categories). When applying logistic regression I have a model that calculates the coefficients of each of ...
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Binary Logistic Regression with both dependent and independent variables
I have a dataset that has a binary dependent variable (choose 1=yes, 2=no) and the reasons given to choose each product. Independent variables include color (1=yes, 2=no), flavor (1=yes, 2=no), etc.
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Do I need to exponentiate coefficients when I use Stata's logistic rather than Stata's logit?
I have a continuous variable and a binary variable. I am conducting logistic regression to see the relationship between them. Is it true that if I use the Stata command ...
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Which statistical test should I use for a relationship between a continuous IV and a binary outcome? What about confounders?
I have a continuous independent variable ($x$) and binary dependent variable ($y$). I want to look at the relationship between them (I think I'd prefer regression to correlation) and I want to see how ...
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Featrue importance according to logistic regression. in python [duplicate]
I've trained a logistic regression over my data. I checked feature importance:
...
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Bayesian Logistic Regression: Correcting for Pre-Experiment Bias
In this post, I will outline a proposed procedure and ask for critical review of the approach's validity. The context is that in a business experiment, it is known that the response variable in the ...
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Marginal effects in logistic regression and subgroup analysis
I am conducting a research project implementing exact matching to seek to isolate a marginal effect of a binary exposure variable on a binary outcome (via MatchIt in R). I am using logistic regression ...
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Why is a logistic regression model using glm() different from a linear model with a logit transformation of the response using lm()?
I've only just started learning logistic regression so bear with me. As I understand it, the logistic regression model is as follows:
$$\log\left(\frac{p(X)}{1-p(X)}\right) = \beta_0 + \beta_1X $$
...
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To nonparemetrically estimate the conditional mean of a binary outcome $E(D|x_1,x_2)$, can I use a logistic regression with flexible regressors?
Suppose $D$ is a binary outcome and $X_1$, $X_2$ are continuous regressors. I want to nonparametrically estiamte $E(D|X_1=x_1,X_2=x_2)$. I know that we could use local-constant or local linear ...
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How do I know if logistic linearity assumption is met based on graphs?
How do I know if my logistic model's numeric variables violate the linearity assumption on the log(target variable)?
I am using the code found at THIS LINK. They graphed on the same data but I, ...
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Logistic Regression with Non Binary Predictors
I have some data where each row has features and an output variable on the interval [0,1]. The output was likely the result of logistic regression, but we have no ...
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How to read interaction coefficients in logistic regression?
How do i read age:gender1?
Gender1 is male.
...
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Sanity checking survival model
I have some basic statistics foundations (Lean Six Sigma, Industrial Engineering in College), but I'm completely new to survival analysis, and relatively new to Data Science. So I'm looking to sanity-...
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How should I check the linearity assumption in logistic regression of complex survey?
I am conducting logistic regression of complex survey, using the survey package in R. Do I need to check the linearity assumption before using ...
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Having to use features which have low correlation with the target
I'm applying LogisticRegression on breastcancer dataset.
Steps : -
1- A correlation matrix resulted in only four features having ...
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Can you use Multilevel Modeling (aka Hierarchical Linear Modeling) with Sequential Linear Modeling?
I have a question regarding the use of Multilevel Modeling (aka Hierarchical Linear Modeling) with Sequential Linear Modeling.
I am trying to perform Sequential Linear Modeling (with a binary outcome) ...
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Decision boundary in Logistic regression?
According to me in logistic regression, we just try to get a line (polynomial)
and then based on which side the point is from that line the sigmoid gives ans>=0.5 or <0.5,
which we then ...
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How to interpret negative association in multivariate analysis?
In no user of antidepressant group, the crude coefficient is 2.20 and the adjusted coefficient is 2.58. How can I interpret this in my thesis because anxiety risk is decreased in the adjusted model?
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How to choose the right predictors and evaluate if a binomial glm model is good?
So, basically I have data with millions of observations on trees. The data was sampled in different time periods, so it is structured in a way that one line contains information on one tree on the ...
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Interpreting the marginal effect for logit regression when the independent variable log transformed variable [duplicate]
I have run probit and logit regression analysis for a model, where the dependent variable is 'Purchase' which takes the value of 1 for purchase, else zero. The independent variable is the log of ...
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Subject-specific effect in mixed_model with interaction
I have two groups of pupils, males and females in a number of schools. So, two-level data, pupils nested in schools. For each gender group, a logistic model was estimated with a school-level predictor ...
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Formula to determine minimum sample size for logistic regression [duplicate]
I was researching logistic regression's critieria, and I found in many different sources that the ideal
sample size = (10 * #of explanatory variables) / (probability of least frequent observations)
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Why We Don't Need Normal distribution on Independent and dependent variables in Logistic Regression?
I am Looking for the Reason That we do not Need Normal distribution on Independent and dependent variables in Logistic Regression, can anybody explain it ?
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Mathematical formula for logistic regression mixed effects model
I am unsure how to write these models in mathematical notation when it is a model with nested random effects. This is how the models were created in R:
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MLE in a logistic regression model
Assuming that the design matrix is of full rank, in non-degenerate cases of the logistic regression model, does the maximum likelihood estimator always exists and is always unique?
It would be really ...
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What can be advantage of ordered logit/probit compare to multinomial logit other than dependent variable format?
I know that in case of some existing dataset whose dependent variable is ordinal, and I want to use it, it is recommended to use ordered choice model than typicall multinomial choice model.
But what ...
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Purpose of regularization in Logistic Regression when dealing with separable data
Our training data will either be linearly separable or non-linear separable. In both cases the decision boundary is defined by:
$$ f(\mathbf{x}) = \mathbf{w} \cdot \mathbf{x} + b = 0 $$
and we ...
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How to pick an appropriate test for a mixed design with an ordinal dependent variable
I am designing a survey project to try to see if image characteristics impact how pictured subjects are viewed by survey respondents.
As the design stands now, each survey respondent will be shown a ...
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Insignificant variable in logistic regression with significant t-test
I have performed a study evaluating the diagnostic performance of a new test (T) (binary outcome) for a disease (D).
Logistic regression was performed with the disease state as a dependent variable, ...
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Is 0.1542 Mcfadden's Pseudo R2 acceptable in general?
I am conducting logistic regression and got 0.1542 as pseudo R2, and it is based on Mcfadden's.
I've searched materials about this, because this is my first time that modelling logit models, and found ...
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Assess too many inter-parameters interactions and combine relevant variables
I'm working on a multicenter prospective cohort study investigating the predictive accuracy of a sepsis score (qSOFA) to predict 30-days in-hospital mortality and using Stata 17 ME. The score has four ...
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Continuous predictor variable has non-linear association with log odds of response
I'd like to know if a continuous predictor variable (sal) predicts a binary response (empty) in a logistic mixed effect model, but discovered there is a non-linear relationship between the predictor ...
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Modeling multiple-choice data
In my experiment, participants had to make a series of decisions between different options. On each trial, they were presented with a different number of options to choose from, and each option varied ...
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How can I figure out why two predictions from the same GLM have different compositions of predicted outcomes?
I'm creating a set of models predicting species presence and absence using binomial GLMs. I created a GLM model from some survey data, and I have made predictive maps for the current and future ...
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How do you interpret $\chi^2$ p-values for a logistic regression, i.e.when R outputs the p-values sequentially with anova(model,test= Chisq)?
How would you interpret this output:
...
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How do I justify this QDA expression for $a_k, ~b_{kj} $and $c_{jkl}$?
I need to solve the equation of
$$\log\left(\frac{\operatorname{Pr}(Y=k|X=x)}{\operatorname{Pr}(Y=K|X=x)}\right)$$
$$=\log\left(\frac{\pi_k \exp\left((x-\mu_k)^T|\Sigma|^{-1}(x-\mu_k)\right)}
{\pi_K \...
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Does it make sense to convert a single dummy variable into a factor?
I have an R lecture script infront of me, where we are using logistic regression to try to predict the probability that an observation belongs to the target class (e.g. y_i = 1) or not (e.g. y_i = 0). ...
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Is Logistic Regression Possible Using a Convenience Sample?
I've collected some survey data on homeless individuals, surveying their drug use, education level, age, gender etc. I hope to run a logistic regression to see how impactful homelessness (+other ...
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Diagnostics of a logistic regression model using Firth's bias reduction method
I fitted a logistic regression model using Firth's bias reduction method. This model is aimed to explore significant factors related to my binary response variable (the outcome with rare events, i.e. ...
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Automatically obtain optimum cutoff point for accuracy, sensitivity and specificity
Below is a code snippet to plot the accuracy, sensitivity and specificity. I can manually eyeball and see the cutoff point at approximately around 0.3. I was wondering if there anyway to print out ...
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How to choose mixed effects (in logistic glmm)
I've constructed a logistic glmm for predicting if individuals of a single species of fish caught will have an empty stomach or not (1=emtpy, 0=not empty). My predictor variables are salinity (sal), ...
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Fisher information matrix for logistic regression using the logit link
A question on a problem sheet I am working on asks us to find the Fisher information matrix (FIM) for the following setup:
Suppose that $Y_i \sim \textrm{Bin}(r_i, \pi_i)$ for $i = 1, 2, \dots , n$, ...
user358331
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Logistic regression with two slopes and one intercept
I am using R to fit a logistic model to some data. The problem is as follows:
"The effects of the dose of poison $(x)$, in milligrammes, and the method of delivery $(w)$ on the
probability of ...
user358331
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Using classification models on censored data?
I have a dataset in which I am trying to predict whether customers default on their loans or do not.
One of my variables is called DURATION which indicates the ...
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