Questions tagged [logistic]
Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression
8,114
questions
2
votes
0
answers
600
views
Logistic regression discrimination threshold with cross validation [duplicate]
I'm using logistic regression to perform binary classification with training, CV, and test sets. When is the most appropriate time to pick a discrimination threshold to balance positive and negative ...
- 33
1
vote
1
answer
2k
views
Logistic Regression Algorithm? [closed]
I am studying on some Machine Learning concepts. I am looking for logistic regression(multiclass) and logistic regression classifier and I should learn how to change it to penalize large weights.
I ...
- 661
4
votes
1
answer
2k
views
Logistic vs linear regression
Let's say I run a linear regression model with a binary dependent variable. If I ran logistic regression on the same data would the results be comparable or exactly similar? By results I mean both the ...
- 817
4
votes
2
answers
2k
views
How do important and insignificant variables impact model?
I am working to build a model using logistic regression. There is one variable which has strong predictive power. But based on business rule, I cannot include this variable in the model. On the other ...
- 43
2
votes
3
answers
1k
views
How to describe characteristics of the curve fit by a four parameter non-linear regression?
I've fit a non-linear mixed effects model with a four parameter logistic function. My specific interest is in characterizing the point on the curve at which the horizontal component of the curve meets ...
- 310
3
votes
1
answer
9k
views
R: mlogit error on data - "system is exactly singular"
So I have data from a randomized blind trial of 1mg of nicotine gum on dual n-back working memory scores; I analyzed them as usual with a t-test and found a small increase in means but a large ...
- 415
3
votes
1
answer
151
views
Experimental Design for Comparative Responses
Suppose I were looking to optimize the amount of certain spices in a chili spice recipe. The textbook experimental design would have me encode the amount of each spice in the design variable, choose ...
- 14.2k
4
votes
2
answers
2k
views
Logistic regression with low event rate
I'm trying to build a logistic regression model to predict 90+ Days past due(DPD) events. The size of the database is 96000, with an event rate of 6%. We ran the entire data set through the info value ...
- 41
37
votes
3
answers
25k
views
Kernel logistic regression vs SVM
As is known to all, SVM can use kernel method to project data points in higher spaces so that points can be separated by a linear space.
But we can also use logistic regression to choose this ...
- 761
1
vote
1
answer
313
views
Aliases in fractional factorial designs
I am looking at using a fractional factorial design in order to reduce the number of treatment runs for an experiment involving a binary outcome. The idea is to create the design, then, since this is ...
- 7,990
1
vote
0
answers
105
views
Regression Analysis model [closed]
Objective is to predict a car's retail value based on the characteristics of mileage, make, model, engine size, interior style, and cruise control.
Price
The price of the vehicle
Cylinder
4,6,8
...
- 21
1
vote
1
answer
599
views
Reference category in multinominal logistic regression
I was wondering how you get beta values for the final model if you don't
have a reference condition?
I am running a multinominal logistic regression using a dependent variable
that has 6 levels - ...
2
votes
1
answer
207
views
How to code values for males when they're only meaningful for females? [duplicate]
I'm building a predictive model for a medical condition that happens in both men and women. Physicians have reported that in some cases for women, their menstrual history seems to be a risk factor, ...
- 2,195
10
votes
1
answer
6k
views
Logistic regression-like model for non-discrete outcomes
If I have a set of continuous predictors $X$ and a binary outcome $Y$ and I wanted to build a predictive model of $P(Y|X)$, I would start with a logistic regression model.
However, in my particular ...
- 1,860
0
votes
1
answer
2k
views
Checking the regression model's performance
I am R-tool beginner. I have a question regarding how to know the performance of a linear regression model by using validation data.
My approach was
Create training and validation data sets from ...
user16603
35
votes
6
answers
61k
views
What is the difference between logistic regression and neural networks?
How do we explain the difference between logistic regression and neural network to an audience that have no background in statistics?
- 798
12
votes
4
answers
10k
views
Extending logistic regression for outcomes in the range between 0 and 1
I have a regression problem where the outcomes are not strictly 0, 1 but rather in the range of all real numbers from 0 to 1 included $Y = [ 0, 0.12, 0.31, ..., 1 ]$.
This problem has already been ...
- 4,288
1
vote
1
answer
2k
views
probability of interest [closed]
The model that I created in R is:
fit <- lm(hired ~ educ + exper + sex, data=data)
what I am unsure of is how to fit to model to predict probability of interest where p = pr(hiring = 1).
Edit:...
- 21
1
vote
4
answers
255
views
What type of regression model do I use?
$y = \mathbf{X} \beta$ + $\epsilon$ + $m$
Where y, $\epsilon$, and $m$ are $n \times 1$ column vectors, $\beta$ is $p \times 1$ and $\mathbf{X}$ is $n \times p$.
$y$ is a noisy time-series signal ...
- 2,761
1
vote
2
answers
531
views
Interactions make terms significant in regression when they should not be
I am writing code to prepare for running a logistic regression on real data. I have sample data for all my IVs but not for the outcome variable. There are many strong dependencies among the IVs but I ...
- 279
1
vote
1
answer
868
views
Algorithm convergence with logistic classifier
I am doing a college classification project, in which I am required to classify some handwritten digits. Assume that my input is a N*D where D is the number of features in each input sample and I need ...
- 217
5
votes
0
answers
405
views
Confidence interval for proportions
I have some data like this:
id pop var
1 593 51
2 592 31
3 346 20
4 1214 70
5 1063 66
6 1370 71
each ...
- 3,414
0
votes
1
answer
660
views
Logistic Regression model keeps kicking out 1 dummy
I have a dataset in which each row belongs to one of 8 categories. I'm running a logistic regrssion on it using R. I created dummy variables for each of these categories. In my logistic regression ...
0
votes
2
answers
157
views
logistic regression always yielding increasing f'n when should sometimes be decreasing (using R)
I'm modeling a set of outcome data the depends on two parameters:
time, T
-100 < A < 100
I've done logistic regression using R with the command:
...
- 93
4
votes
0
answers
552
views
Sensible to include ratio as a variable in logistic regression?
I'm creating a generalised linear regression using a binomial link function for
two variables A and B. From looking at the data it appears that A/B may have
discriminatory effect. Is it sensible to ...
- 373
2
votes
2
answers
1k
views
Logistic regression: big difference in predicted values and highly significant, but poor goodness of fit
I have a logistic regression model with a dichotomous response variable and predictors coded from $1$ to $10$ and from $0$ to $18$.
When I fit the model, I get these results:
...
- 21
14
votes
2
answers
7k
views
poisson vs logistic regression
I have a cohort of patients with different length of follow-up. So far I´m disregarding the time aspect and just need to model a binary outcome-disease/no disease. I usually do logistic regression in ...
- 1,293
1
vote
0
answers
306
views
Whether to use linear regression or not
Effects of growth hormone (GH) replacement with recombinant human GH on bone and mineral metabolism were studied in 36 GH-deficient children. Several outcomes, including serum ionized calcium levels, ...
- 11
1
vote
0
answers
977
views
When the response variable is a proportion (r/n) in proc logistic, how to express the model in terms of $\pi, \alpha, \beta$?
A (SAS documentation file) (page 1906) on "The LOGISTIC Procedure" gives the following procedure-
proc logistic;
model r/n=x1 x2;
run;
Here, n represents the ...
- 11
1
vote
1
answer
119
views
Adding not chosen alternatives as data to logistic regression model
I am interested in predicting shopping behaviour in a shopping center. I have a database with the chosen alternatives (shop) and variables describing that alternative (like type and size) and the ...
- 445
9
votes
4
answers
9k
views
Choosing between logistic regression and Mann Whitney/t-tests
I have a dichotomous variable $A$, which does not have an a priori determined proportion of 0's and 1's, and a continuous variable $b$.
In scenario 1, I decide to designate $A$ as the independent ...
- 407
6
votes
1
answer
1k
views
Shifted intercepts in logistic regression
I have a question about the effects of shifting the intercept in a logistic fit on the mean of a particular transformation of the scores.
Here is the notation I will be using for the question. The ...
- 8,582
0
votes
3
answers
2k
views
"Wrong Sign" On Regression Coefficients - Hierarchical Multiple Linear Regression
I am analyzing my data on the relationship between spirituality and negative emotional states (depression, anxiety, and stress) using a hierarchical multiple linear regression. Everything seemed to be ...
- 401
1
vote
0
answers
827
views
Why am I getting a zero parameter estimate and SE for one of my variables in a logistic regression?
I am doing a binary logit analysis, in which I'm trying to fit a model to my data to explain why some towns adopt open space subdivision ordinances (OP), using a handful of discrete and continuous ...
- 11
0
votes
1
answer
3k
views
How to calculate 95% CI for OR for a different reference category without running the SAS logistics again?
My question is about calculation of confidence interval (CI) for odds ratio (OR) from a SAS output of a logistic regression model for a different reference category without running the SAS program ...
- 11
3
votes
1
answer
356
views
Which model to use with repeated measures data that contains multiple binary dependent variables
What model should I use??? I have daily repeated measures data. It has multiple dependent presence absence variables, (of which, I have collapsed into a CA with continuous variables of CA1 & CA2....
- 51
13
votes
1
answer
15k
views
Predicting ordered logit in R
I'm trying to do an ordered logit regression. I'm running the model like so (just a dumb little model estimating number of firms in a market from income and population measures). My question is ...
- 536
3
votes
0
answers
516
views
Is there a better alternative to a logit / probit regression when all dependent variables are dichotomous?
I'm working on a clinical trial dataset with binary response. All independent variables are also binary. My first impulse was to simply run a standard logit / probit regression and be done with it. ...
2
votes
0
answers
428
views
Polynomial kernel in logistic regression?
So I have put together a nice logistic regression program that works quite well. Now, I have used two dimensions to test it and see how it works, and guided by some online tutorials, have increased ...
- 235
92
votes
4
answers
61k
views
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 ...
- 1,872
12
votes
1
answer
9k
views
Can I interpret the inclusion of a quadratic term in logistic regression as indicating a turning point?
In a Logistic Regression with linear and quadratic terms only, if I have a linear coefficient $\beta_1$ and quadratic coefficient $\beta_2$, can I say that that there is turning point of the ...
- 121
4
votes
0
answers
9k
views
How to diagnose multicollinearity using the output of vif function in R?
I am running a logistic regression in R and am attempting to determine if multicollinearity is a problem with my model.
When I run vif() on my final model, I get <...
- 173
2
votes
1
answer
1k
views
How to encode factors as dummy variables when using stepPlr?
When using the step.plr() function in the stepPlr package, if my predictors are factors, do I need to encode my predictors as dummy variables manually before ...
0
votes
1
answer
2k
views
Logistic regression on a dataset with duplicated records
I have a large data set with multiple records per phone number. Each record has two variables - the number of past attempts in the past 60 days (number of times it was called) which range from 0 to 30 ...
- 7,990
2
votes
1
answer
3k
views
Logistic growth inflection point
I have a logistic growth curve as follows:
$y = \frac{1}{(1 + ae^{-bx})}$, where x is the independent measure (x-axis) and a and b are paramaters. The inflection point of this equation is when y = 0....
- 473
1
vote
1
answer
855
views
How to determine the best relationship (linear, log, etc.) between input predictor variable(s) and output variable for multiple linear regression?
I am trying to determine the most accurate relationship between two variables (each predictor versus the output eventually). I want to know if the relationship is linear, or log-linear, or log-log, or ...
- 11
2
votes
2
answers
2k
views
Regression with repeated measures in Matlab
Is there a way to perform multiple logistic regression on repeated measures data using Matlab?
I have a data set containing a daily measurement recorded from 20 participants for 60 days. I am ...
- 3,223
2
votes
0
answers
230
views
Reporting contrasts between binary probability parameters in Bayesian data analysis - odds ratios or difference in probability?
In a bayesian data analysis, if one is modeling differences in binomial/bernoulli probability parameter differences between populations, is it still standard to report the difference in the binary ...
- 2,574
6
votes
3
answers
1k
views
Which logit or probit model should I use for multiple response / dependent variables?
I have $300$ time series objects that constitute the $300$ columns of matrix $X$. This matrix has $5$ rows and represents $5$ days of time series information for each $300$ columns.
I set up a $300\...
user14281