Tagged Questions
1
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1answer
37 views
Which bootstrapped regression model should I choose?
I have a binary logistic regression model with a DV (disease: yes/no) and 5 predictors (demographics [age, gender, tobacco smoking (yes/no)], a medical index (ordinal) and one random treatment ...
0
votes
0answers
15 views
OK to use residual sum of squares for cross-validation of binary outcome?
For an OLS model the mean squared error can be used to assess the fit of the trained model on the validation data.
What is the equivalent for a logistic regression model? Can I simply use the ...
0
votes
1answer
16 views
can EM algorithm be applied to my problem? Input data set is based on a function of parameter
I understand EM algorithm is often used for missing data/mixture problem. But can it be used to optimize a particular type of likelihood based on jointly fitting variables and transformations of those ...
0
votes
1answer
54 views
Logistic regression: controlling variables not significant, what should I conclude/further test? [closed]
I ran annual logisitic regression on time-series datas. The most important independant variable have coefficient that are significant in a lot of years, that's a relief. But the "controlling ...
1
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0answers
23 views
Nested vs. conditional logit regression
I am trying to estimate a logit regression model with travel mode choice (categorical) being the dependent variable; explanatory variables include age (categorical), income (categorical), gender ...
3
votes
0answers
39 views
Generalization of cumulative probability models for ordinal Y
There are many models in existence for ordinal $Y$, for example the proportional odds ordinal logistic model, the continuation ratio model, and the cumulative probit model. The first and third of ...
2
votes
0answers
33 views
How to report most important predictors using glmnet?
I want to find the most important predictors for a binomial dependent variable out of a set of more than 43,000 independent variables (These form the columns of my input dataset). The number of ...
0
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0answers
35 views
Logistic regression with random and with fixed intercept
I have made logistic regression with fixed intercept and with random intercept on the same data, and the results (the odds-ratios) are very different. Could somebody tell me what can be the reasons of ...
0
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0answers
17 views
Prepare data for generalized linear regression [migrated]
I want to perform glm for the dataset Titanic in R. I did the following steps to prepare the data and run glm
...
0
votes
1answer
33 views
spss: working with two binary/dummy variables
Am trying to set a few binary/dummy variables against each other, i.e. propensity_to_dance and gender.
I assume that it' ok to ...
0
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0answers
21 views
spss 20 for mac: how to get probabilities after running a binary logistic regression [duplicate]
I have a binary variable that I'm investigating in SPSS, inclination_to_dance. I have another linear variable as well, ...
3
votes
2answers
68 views
Is this a case for ordered logistic regression?
I have the following study setup:
Three groups of people were asked a question, and the answer was ordinal (likely, somewhat likely, somewhat unlikely, unlikely). In my data set, I have a contingency ...
0
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0answers
10 views
Debugging Multinomial Logistic Regression Implementation [migrated]
Hi for the University we are required to implement from scratch (using numpy / scipy) Multi-logit. So basically I have to implement the log-likelihood and the graditen of that function.
I have ...
0
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0answers
28 views
Zero logit coefficient
Multinomial regression output gave me zero logit coefficients for continuous independent variables of income and saving. What could be the reasons for this?
Secondly, zero cell in the multinomial ...
0
votes
2answers
126 views
Is there a simple rule for interpretation of Interactions (and their directions) in binary logistic regression? [duplicate]
I have a binary logistic regression with Y (a disease) and 5 independent variables (and some of their 2-sided interactions which did not cause multicollinearity). All of my single IVs significantly ...
3
votes
0answers
56 views
Analysis of randomized experiments
I have data from an experiment in which participants were randomly assigned to one of two groups and asked a series of opinion questions. One group, the control, was not presented with any additional ...
1
vote
1answer
41 views
What to do With Curvilinear Relationships?
If I have determined a curvilinear relationship between my dichotomous y and continuous x, what should I do before running a logit regression?
Should I log transform my x variable, etc?
3
votes
1answer
47 views
Recreate logistic regression equation from table of odds data
I'm reading the technical manual for a linking study between two assessments. It's pretty clear that the table is model output from a fitted logistic regression equation. Here's what pass odds look ...
1
vote
2answers
90 views
Fit a logistic regression code in R
If I have 10 Variables (Q,W,E,R,T,Y,U,I,P,A) and I want Q to be my response variable and other 9 to be my predictors variable. Do I write it in R like this
...
2
votes
1answer
28 views
Nested Models for Likelihood Test
If I have a logistic regression model with 3 predictors, $x_1$, $x_2$, $x_3$, and then I remove $x_3$ from my model (left with only $x_1$ and $x_2$), are those models nested? And therefore I can use ...
4
votes
1answer
201 views
Meaning of p-Value of logistic regression model variables
So I'm working with logistic regression models in R. Though I'm still new to statistics I feel like I got a bit of an understanding for regression models by now, but there's still something that ...
0
votes
1answer
71 views
Obtaining base level with margeff & gologit2 in STATA
I would be extremely glad if someone could help me with this.
I'm using the gologit2 generalized logistic regression/ partial proportional odds model for ordinal dependent variables. The dependent ...
0
votes
0answers
20 views
Output of logistic regression model [duplicate]
I have built a logistic regression model using SPSS to predict a variable (0 or 1)
The coefficients are as below: -0.005, 0.132, 1.349, -1.321,-0.265,-0.981, intercept = -1.522 when I sub in the ...
1
vote
1answer
25 views
Calculating trend for 3 dimensional data
Forgive me for a potential dupe, as I don't know the correct terminology for searching for an existing question. Also please add tag "trends" or similar, as I don't have the reputation to create new ...
0
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0answers
40 views
Binomial logistic regression in Java
does anyone have any idea of a Java library that performs binomial logistic regression? i've looked at the Kazanova, Weka libraries but does anyone know of any other?
thanks
0
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0answers
32 views
Convergence of batch gradient descent in logistic regression
I am not really sure about how it behaves when using batch gradient descent in logistic regression.
As we do each iteration, $L(W)$ is getting bigger and bigger, it will jump across the largest point ...
1
vote
1answer
37 views
Regression Estimation difficulties
My regression problem is properly formulated, but is encountering serious computational difficulties.
Dependent: $Y$ = multinomial
Independent: $X_1, \dots, X_{90}$ = linearly independent set of ...
1
vote
2answers
79 views
Explain overfitting / data leakage to a colleague
I have a situation where we are calculating a customer life time value using some binary variables (ie have they purchased xyz widget?, etc.) and multiplying by a number that we believe approximates ...
1
vote
0answers
56 views
How to implement a fractional polynomial transformation in R for logistic regression
I'm working on a data set modeling road kills (0 = random point, 1 = road kill) as a function of a number of habitat variables. Following Hosmer and Lemeshow, I've examined each continuous predictor ...
1
vote
0answers
39 views
performing logistic regression with imputed variables
I am trying to to run a logistic regression (case-control) and the variable of interest is categorical, taking the values 0 to 6. For a subset of individuals, I do not have the exact value (0, 1 .. or ...
3
votes
1answer
54 views
Applying Recency In Logistic Regression
Are there any statistical concepts or theories on how to effectively measure recency to where recent events are given more weight than older ones. I'm creating a logistic regression model and would ...
1
vote
3answers
171 views
Reporting of an interaction in a binary logistic regression
I've found some interesting results that I'm trying to write up appropriately, but I'm having a hard time finding any guidance into how to write up an interaction in a binary logistic regression ...
0
votes
0answers
59 views
Dealing with problems of logistic regression
How powerful is logistic regression as the main tool for statistical analysis of a study? It seems to have certain problems:
There are non normal error terms
We have non constant error variance
...
2
votes
2answers
143 views
In my logistic regression model one of the independent variables is redundant with the interaction term. How should I deal with it?
In my logistic regression is the dependent variable a dummy variable and I also have two independent variables. One of those is a dummy variable and the other is a metric variable. I also suppose an ...
3
votes
2answers
175 views
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 ...
1
vote
1answer
144 views
How to interpret statistics (Emax, D, U, Q, B, etc.) of bootstrap validation of logistic regression
I'm only a linguist, so my knowledge of statistics is very basic.
I fitted a logistic regression model with R (with lrm(formula, y=T, x=T)), and when I use the ...
0
votes
0answers
19 views
Change in S.E of one variable when interaction term added to Binary Logistic Regression [duplicate]
I have 6 predictor variables and have carried out a binary logistical regression. I found that most variables significantly predicted the DV. However, I then wanted to find out if there was a ...
1
vote
3answers
51 views
Which test(s) for analyzing yes-no answers for control vs treated conditions
To keep it simple, I have sets of data in which I have a control and a treated sample. The data I obtain is "yes" or "no" (0 or 1) for a particular behaviour. I have 150 data points for each condition ...
2
votes
1answer
141 views
Logistic regression as classifier and overfitting
I am using logistic regression to classify data into two classes. The variable to predict (Y) is either 0 or 1.
I have found a rather good estimation of Y by logistic regression, and ended up using ...
0
votes
2answers
171 views
Binomial GLM and different sample sizes
I have a data set which consists of binomial proportions, let's say the success rate of converting a customer depending on the advertisement, the customer age, and various other factors.
For some ...
0
votes
1answer
138 views
Ordinal dependent variable with continuous independent variables
I have an ordinal dependent variable, named D, which varies from very small, small, medium, big, to very big. This variable depends on the independent variables X, V, which are continuous variables. ...
0
votes
1answer
83 views
Modeling a outcome variable heavily skewed toward 0
I am working with a data set to model student performance with various variables from the class/school/district/provincial level. Student performance is extremely low though--~70% of reading ...
0
votes
0answers
29 views
Replicates in logistic regression: identifying significant factors
I'm investigating whether the factors Height (3 levels) and Distance (3 levels) have a significant effect on the proportion of females that are mated by males radiating from a central source. My ...
3
votes
0answers
85 views
Using priors to detect an effect? logistic Bayesian regression
I have designed an idea and am looking for similar approaches in other literature/areas or if I have applied the Bayesian concepts wrongly. Here is a statement of my problem:
I am modeling the ...
1
vote
0answers
69 views
Conditional analysis” vs “Conditional logistic regression
What is the difference between "Conditional analysis" and "Conditional logistic regression"?
It is also really hard to find out an easy example of that "Conditional" means in this case...
1
vote
1answer
160 views
If using interval data (independent variables) and grades (outcome or dependent variable), what type of analysis would one use?
First of all, my background in statistics is a bit shaky these days due to a trauma to the brain. I am considering a study that examines at least three independent variables (e.g., creativity, locus ...
2
votes
0answers
54 views
How to get SGD to reach global optimal point in logistic regression?
I am trying to write a tool which involves implementing logistic regression. With the batch gradient descent method, the convergence is guaranteed as it is a convex problem. However, I find that with ...
1
vote
0answers
107 views
Is conditional logit a specific form of GLM? And what are its specificities?
Background: For a project, I am fitting a conditional logit model where I have 5 control cases for every realized case. To do that I use the clogit() function in ...
1
vote
1answer
93 views
Estimate just the constant coefficient in logistic regression
How do I calculate the constant coefficient in logistic regression manually, i.e without having to use a calculator?
My model is
$g(Y) = X \beta + \alpha$
is it possible to calculate just the ...
5
votes
3answers
534 views
How to interpret a logistic regression model with all negative coefficient?
I have 4 predictors, and 1 binary response. I fitted a logistic regression model. A strange thing is that all the coefficient of the model are negative. Is that possible? Probably I did something ...
