Skip to main content

Questions tagged [logistic]

Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression

Filter by
Sorted by
Tagged with
211 votes
9 answers

How to deal with perfect separation in logistic regression?

If you have a variable which perfectly separates zeroes and ones in target variable, R will yield the following "perfect or quasi perfect separation" warning message: ...
user333's user avatar
  • 7,241
393 votes
12 answers

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 ...
Beta's user avatar
  • 6,356
125 votes
3 answers

Does an unbalanced sample matter when doing logistic regression?

Okay, so I think I have a decent enough sample, taking into account the 20:1 rule of thumb: a fairly large sample (N=374) for a total of 7 candidate predictor variables. My problem is the following: ...
Michiel's user avatar
  • 1,353
31 votes
1 answer

Omitted variable bias in logistic regression vs. omitted variable bias in ordinary least squares regression

I have a question about omitted variable bias in logistic and linear regression. Say I omit some variables from a linear regression model. Pretend that those omitted variables are uncorrelated with ...
ConfusedEconometricsUndergrad's user avatar
119 votes
4 answers

Why isn't Logistic Regression called Logistic Classification?

Since Logistic Regression is a statistical classification model dealing with categorical dependent variables, why isn't it called Logistic Classification? Shouldn't the "Regression" name be reserved ...
Ismael Ghalimi's user avatar
37 votes
2 answers

Interpretation of simple predictions to odds ratios in logistic regression

I'm somewhat new to using logistic regression, and a bit confused by a discrepancy between my interpretations of the following values which I thought would be the same: exponentiated beta values ...
mike's user avatar
  • 867
72 votes
9 answers

Which pseudo-$R^2$ measure is the one to report for logistic regression (Cox & Snell or Nagelkerke)?

I have SPSS output for a logistic regression model. The output reports two measures for the model fit, Cox & Snell and ...
Henrik's user avatar
  • 14.2k
64 votes
1 answer

Logistic regression in R resulted in perfect separation (Hauck-Donner phenomenon). Now what? [duplicate]

I'm trying to predict a binary outcome using 50 continuous explanatory variables (the range of most of the variables is $-\infty$ to $\infty$). My data set has almost 24,000 rows. When I run ...
Dcook's user avatar
  • 773
44 votes
2 answers

Simulation of logistic regression power analysis - designed experiments

This question is in response to an answer given by @Greg Snow in regards to a question I asked concerning power analysis with logistic regression and SAS ...
B_Miner's user avatar
  • 8,780
67 votes
4 answers

Regression for an outcome (ratio or fraction) between 0 and 1

I am thinking of building a model predicting a ratio $a/b$, where $a \le b$ and $a > 0$ and $b > 0$. So, the ratio would be between $0$ and $1$. I could use linear regression, although it doesn'...
dfrankow's user avatar
  • 3,386
58 votes
1 answer

Why do my p-values differ between logistic regression output, chi-squared test, and the confidence interval for the OR?

I have built a logistic regression where the outcome variable is being cured after receiving treatment (Cure vs. No Cure). All ...
SniperBro2000's user avatar
103 votes
5 answers

How to calculate Area Under the Curve (AUC), or the c-statistic, by hand

I am interested in calculating area under the curve (AUC), or the c-statistic, by hand for a binary logistic regression model. For example, in the validation dataset, I have the true value for the ...
Matt Reichenbach's user avatar
37 votes
6 answers

Sample size for logistic regression?

I want to make a logistic model from my survey data. It is a small survey of four residential colonies in which only 154 respondents were interviewed. My dependent variable is "satisfactory transition ...
Braj-Stat's user avatar
  • 621
48 votes
1 answer

Does down-sampling change logistic regression coefficients?

If I have a dataset with a very rare positive class, and I down-sample the negative class, then perform a logistic regression, do I need to adjust the regression coefficients to reflect the fact that ...
Zach's user avatar
  • 24k
28 votes
2 answers

What is happening here, when I use squared loss in logistic regression setting?

I am trying to use squared loss to do binary classification on a toy data set. I am using mtcars data set, use mile per gallon and weight to predict transmission ...
Haitao Du's user avatar
  • 37.1k
14 votes
2 answers

Bayesian logit model - intuitive explanation?

I must confess that I previously haven't heard of that term in any of my classes, undergrad or grad. What does it mean for a logistic regression to be Bayesian? I'm looking for an explanation with a ...
BCLC's user avatar
  • 2,444
140 votes
3 answers

What is the difference between linear regression and logistic regression?

What is the difference between linear regression and logistic regression? When would you use each?
B Seven's user avatar
  • 2,933
53 votes
1 answer

Regression: Transforming Variables

When transforming variables, do you have to use all of the same transformation? For example, can I pick and choose differently transformed variables, as in: Let, $x_1,x_2,x_3$ be age, length of ...
Brandon Bertelsen's user avatar
34 votes
3 answers

How to handle ordinal categorical variable as independent variable

I am using a logit model. My dependent variable is binary. However I have an independent variable which is categorical and contains the responses: ...
rahmat's user avatar
  • 341
5 votes
1 answer

Logistic regression with poor goodness of fit (hosmer lemeshow)?

I built a model with 9 categorical predictor variables. Using SPSS, my omnibus test was significant ($\chi^2$=220.01), my -2loglikelihood was 1335.2 (Nagelkerke $R^2$ 0.231), but my Hosmer and ...
Tamara29's user avatar
  • 111
57 votes
2 answers

How to simulate artificial data for logistic regression?

I know I'm missing something in my understanding of logistic regression, and would really appreciate any help. As far as I understand it, the logistic regression assumes that the probability of a '1' ...
zorbar's user avatar
  • 767
15 votes
1 answer

Interpretation of Fixed Effects from Mixed Effect Logistic Regression

I am confused by statements at a UCLA webpage about mixed effects logistic regression. They show a table of fixed effects coefficients from fitting such a model and the first paragraph belows seems to ...
B_Miner's user avatar
  • 8,780
116 votes
4 answers

What is rank deficiency, and how to deal with it?

Fitting a logistic regression using lme4 ends with Error in mer_finalize(ans) : Downdated X'X is not positive definite. A likely cause of this error is ...
Jack Tanner's user avatar
  • 4,862
27 votes
1 answer

Help me understand adjusted odds ratio in logistic regression

I've been having a hard time trying to understand the use of logistic regression in a paper. The paper available here uses logistic regression to predict probability of complications during cataract ...
mahonya's user avatar
  • 1,111
10 votes
5 answers

Coefficient changes sign when adding a variable in logistic regression

In my logistic regression the sign of coefficients of a variable (location distance of an amenity) changes based on other variables (with time -ve, with travel distance +ve) in the model. When the ...
aruna r's user avatar
  • 323
44 votes
2 answers

Interpretation of plot (glm.model)

Can anyone tell me how to interpret the 'residuals vs fitted', 'normal q-q', 'scale-location', and 'residuals vs leverage' plots? I am fitting a binomial GLM, saving it and then plotting it.
Summer's user avatar
  • 441
39 votes
4 answers

Why does logistic regression become unstable when classes are well-separated?

Why is it that logistic regression becomes unstable when classes are well-separated? What does well-separated classes mean? I would really appreciate if someone can explain with an example.
Jane Dow's user avatar
  • 491
24 votes
1 answer

What is the difference between logistic regression and Fractional response regression?

As far as I know, the difference between logistic model and fractional response model (frm) is that the dependent variable (Y) in which frm is [0,1], but logistic is {0, 1}. Further, frm uses the ...
newbie's user avatar
  • 425
98 votes
4 answers

What is the difference between a "link function" and a "canonical link function" for GLM

What's the difference between terms 'link function' and 'canonical link function'? Also, are there any (theoretical) advantages of using one over the other? For example, a binary response variable ...
steadyfish's user avatar
  • 1,962
28 votes
2 answers

Significance of categorical predictor in logistic regression

I am having trouble interpreting the z values for categorical variables in logistic regression. In the example below I have a categorical variable with 3 classes and according to the z value, CLASS2 ...
user695652's user avatar
  • 1,601
13 votes
2 answers

Significant predictors become non-significant in multiple logistic regression

When I analyze my variables in two separate (univariate) logistic regression models, I get the following: ...
Annie's user avatar
  • 131
56 votes
3 answers

Regularization methods for logistic regression

Regularization using methods such as Ridge, Lasso, ElasticNet is quite common for linear regression. I wanted to know the following: Are these methods applicable for logistic regression? If so, are ...
Tapan Khopkar's user avatar
31 votes
4 answers

What is the relationship between regression and linear discriminant analysis (LDA)?

Is there a relationship between regression and linear discriminant analysis (LDA)? What are their similarities and differences? Does it make any difference if there are two classes or more than two ...
zca0's user avatar
  • 861
73 votes
3 answers

Logistic Regression - Error Term and its Distribution

On whether an error term exists in logistic regression (and its assumed distribution), I have read in various places that: no error term exists the error term has a binomial distribution (in ...
user61124's user avatar
  • 733
10 votes
3 answers

Multiple logistic regression power analysis

I have a logistic regression model and output an $R^2$ value. I then go and add another predictor variable to fit a second model. I can output a new $R^2$ value associated with the second model. When ...
lukeg's user avatar
  • 431
59 votes
4 answers

Multinomial logistic regression vs one-vs-rest binary logistic regression

Lets say we have a dependent variable $Y$ with few categories and set of independent variables. What are the advantages of multinomial logistic regression over set of binary logistic regressions (i....
Tomek Tarczynski's user avatar
39 votes
3 answers

How to do logistic regression in R when outcome is fractional (a ratio of two counts)?

I'm reviewing a paper which has the following biological experiment. A device is used to expose cells to varying amounts of fluid shear stress. As greater shear stress is applied to the cells, more of ...
thecity2's user avatar
  • 1,955
58 votes
2 answers

Interpretation of R's output for binomial regression

I'm quite new on this with binomial data tests, but needed to do one and now I´m not sure how to interpret the outcome. The y-variable, the response variable, is binomial and the explanatory factors ...
user40116's user avatar
  • 701
7 votes
2 answers

How to use boxplots to find the point where values are more likely to come from different conditions?

I have plotted some data using box plots. I am comparing Condition 1 (left) and Condition 2 (Right) values. My aim is to find a point at which we make a decision where the value changes from point ...
Umar's user avatar
  • 151
6 votes
1 answer

T-tests, manova or logistic regression - how to compare two groups?

I'd like to check whether women and men differ on those five variables, that can be correlated with each other. The groups are also not equal with 589 females and 293 males. The solutions that come to ...
Lil'Lobster's user avatar
  • 1,478
43 votes
2 answers

When is logistic regression solved in closed form?

Take $x \in \{0,1\}^d$ and $y \in \{0,1\}$ and suppose we model the task of predicting y given x using logistic regression. When can logistic regression coefficients be written in closed form? One ...
Yaroslav Bulatov's user avatar
60 votes
3 answers

Why is there a difference between manually calculating a logistic regression 95% confidence interval, and using the confint() function in R?

Dear everyone - I've noticed something strange that I can't explain, can you? In summary: the manual approach to calculating a confidence interval in a logistic regression model, and the R function <...
Andrew's user avatar
  • 6,258
28 votes
1 answer

Is there any intuitive explanation of why logistic regression will not work for perfect separation case? And why adding regularization will fix it?

We have many good discussions about perfect separation in logistic regression. Such as, Logistic regression in R resulted in perfect separation (Hauck-Donner phenomenon). Now what? and Logistic ...
Haitao Du's user avatar
  • 37.1k
13 votes
2 answers

Logistic regression and ordinal independent variables

I have found this post: Yes. The coefficient reflects the change in log odds for each increment of change in the ordinal predictor. This (very common) model specification assumes the the predictor ...
Frederico's user avatar
  • 133
3 votes
1 answer

What to do in a multinomial logistic regression when all levels of DV are of interest?

I am running a multinomial logistic regression. The outcome variable is categorical with seven levels. The predictor is binary. Very briefly, the experiment is such that I am asking whether a ...
Dave's user avatar
  • 2,631
132 votes
4 answers

Softmax vs Sigmoid function in Logistic classifier?

What decides the choice of function ( Softmax vs Sigmoid ) in a Logistic classifier ? Suppose there are 4 output classes . Each of the above function gives the probabilities of each class being the ...
mach's user avatar
  • 1,815
80 votes
3 answers

Diagnostics for logistic regression?

For linear regression, we can check the diagnostic plots (residuals plots, Normal QQ plots, etc) to check if the assumptions of linear regression are violated. For logistic regression, I am having ...
ialm's user avatar
  • 1,827
54 votes
1 answer

Obtaining predicted values (Y=1 or 0) from a logistic regression model fit

Let's say that I have an object of class glm (corresponding to a logistic regression model) and I'd like to turn the predicted probabilities given by ...
tetragrammaton's user avatar
50 votes
2 answers

Logistic regression model does not converge

I've got some data about airline flights (in a data frame called flights) and I would like to see if the flight time has any effect on the probability of a ...
Daniel Standage's user avatar
47 votes
3 answers

Logistic Regression: Bernoulli vs. Binomial Response Variables

I want to perform logistic regression with the following binomial response and with $X_1$ and $X_2$ as my predictors. I can present the same data as Bernoulli responses in the following format. The ...
A Scientist's user avatar

2 3 4 5