Questions tagged [logistic]
Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression
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Report coefficients or odds ratio in ordinal logit/probit?
I'm doing ordinal logit/probit only to analyse the direction of causality (e.g. if some variable makes it more likely to observe a low scale or a high scale). No interpretation is needed beyond this.
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Common parameters for conditional likelihood
I am trying to understand the concept of conditional likelihood in the context of logistic regression.
One paper I am reading defines $L(\theta; y|x) = f(y|x; \theta)$, then goes on to point out ...
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How to estimate the deposit mix of a bank using interest rate as the independent variable?
Let's say a bank has 5 different types of deposits. One type is certificates of deposits (CD), and the other 4 types are different checking and savings account products with various interest rates ...
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Negative coefficient in ordered logistic regression
Suppose we have the ordinal response $y:\{\text{Bad, Neutral, Good}\} \rightarrow \{1,2,3\}$ and a set of variables $X:=[x_1,x_2,x_3]$ that we think will explain $y$. We then do an ordered logistic ...
user14281
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Using multinomial regression's coefficients to derive predicted outcomes in C#
I am attempting to use C# (and the alglib library) to calculate the predicted probability that an outcome ends up in one of five classes. I have managed to calculate parameter estimates (i.e. slope ...
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Does learning rate have additional meaning in logistic regression?
I try to implement logistic regression with auto-correcting learning rate and I am puzzled by the outcome.
At some point the cost of the function gets bigger than previously (to focus on some numbers ...
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How do you get lmFuncs functions of the rfe function in caret to do a logistic regression?
I've been experimenting with the rfe function in the caret package to do logistic regression with feature selection. I used the <...
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How to interpret the odds ratio in a logistic regression with proportion as a response variable
I have a glm model for some data with a proportion as the outcome variable as follows:
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Error distribution for linear and logistic regression
With continuous data, a linear regression $Y=\beta_1+\beta_2X_2+u$ assumes that the error term is distributed N(0,$\sigma^2$)
1) Do we assume that Var(Y|x) is likewise ~N(0,$\sigma^2$)?
2) What is ...
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Logistic regression: fixed effects for firms, countries & years
I am trying to use logistic regression on a sample of 20,000+ firms across 50+ countries, from 2000-2010. Do I need to use logistic regression with fixed effects for year and firm + dummy variables ...
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Why is there no analytic solution for logistic regression? [duplicate]
Possible Duplicate:
When is logistic regression solved in closed form?
Why is there no analytic solution for logistic regression?
I was trying to derive a solution similar to the normal equations ...
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How to compare whether models built using two different outcomes are significantly different
I would like to build the relationship between the dose given and two outcomes (one acute toxicity and one late toxicity). The model I used was binary logistic regression. For the acute toxicity ...
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What does a chi-square test mean when no p-value is returned?
I did multinomial logistic regression using SPSS chi-square is .000 , df is 0 and significance =.
So what does it mean significance = .?
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Understand how to test a Logit model on new data
I am having some difficulty understanding something. Let's say that I have data and construct a logit model on that data. Now, let's say I have a similar and newer data set with those same variables, ...
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How to estimate an upperbound for logistic regression by only 5 to 7 data points?
I have data that is of the form $y = \frac{\beta_1}{1 + \exp(\beta_2 + \beta_3 * x)}$. For the estimation of $\beta_1$ to $\beta_3$ I use the formulas of this paper: John Fox - Nonlinear Regression ...
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SAS PROC LOGISTIC: Hosmer and Lemeshow test is good but Gini is bad?
I am using PROC LOGISTIC along with Class statements to do binary logit model(default=1,non-default=0) on a bank loan dataset ...
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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 ...
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Logistic regression: the standard deviation used in: GLMPOWER
I attended a training class from SAS about experimental design in marketing. They advocated the use of their GLMPOWER proc for power analysis for designing experiments.
GLMPOWER is a power analysis ...
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Comparing coefficients in logistic regression
I have some problems I need help with. I am running a binary logistic regression.
...
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Contribution of each covariate to a single prediction in a logistic regression model
Say, for example, that we have a logistic regression model which outputs the probability that a patient will develop a particular disease based on many covariates.
We can get an idea of the ...
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Binomial / multinomial logistic regression or chi-squared
I am currently doing my fourth year thesis examining the moral stages of children/adolescents. The DV is the moral stage (categorical variable, stages 1, 2, 3, or 4) and the IVs are age group (I ...
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Can a contingency table be used to model probabilities?
Its been a while since I did any serious statistics. I have been reading about contingency tables recently and it seems like they may offer a solution to my problem. There are people on here that know ...
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Nested logistic regression in R
I am trying to find a way to do Nested Logistic Regression in R that fits my needs. I have a very large data set with almost 200 variables available. I have found my "best" model and it contains 12 ...
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How can I test for significance of a treatment in an unbalanced, repeated-measures experiment using R?
CrossValidated Community,
I must mention that I am a first-time poster (and relatively new to both modelling and R), so please excuse any norms I may violate in my post and politely inform me.
I ...
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Validation of logistic regression - goodness of fit (pearson)
I have developed a scoring system using logistic regression. The score ranges between 0 and 6 (using integers) and predicts death. It does not use a conventional regression formula and thus I am not ...
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How to justify the use of categorical variables as continuous variables in logistic regression?
One question again to be clarified: Can I use the variables as noted below [(3) a,b,c etc] as continuous variables in my logistic regression and if so what will be my explanation in the paper that I ...
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Test effect of variable across sub-groups logistic regression
I have a logit model where I am predicting stunting (a binary indicator of malnutrition), and my two binary independent variables (improved.water and has.insurance) are both statistically significant: ...
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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 ...
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Fewer variables have higher R-squared value in logistic regression
I am testing out 3 modeling approaches for malnutrition in children. Theoretically, distal determinants (education,poverty) operate through proximal determinants (water, sanitation) in determining ...
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Testing for useful variables in a "net lift model"
I am often involved in modeling the Net lift, aka Uplift, aka incremental response of direct marketing campaigns. In a nutshell, this approach looks to model and thus select for marketing those ...
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Exponentiated logistic regression coefficient different than odds ratio
As I understand it, the exponentiated beta value from a logistic regression is the odds ratio of that variable for the dependent variable of interest. However, the value does not match the manually ...
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How to fix a coefficient in an ordinal logistic regression without proportional odds assumption in R?
I want to do an ordinal logistic regression in R without the proportionality odds assumption. I know this can be done directly using vglm() function in ...
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Can we simply compare the predicted percentages of the outcome between studies?
I used the multinomial logistic regression to predict the percentages of students who voted 'acceptable', 'uncertain', and 'unacceptable' to natural ventilation use in three observed classrooms during ...
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Advice on regression modelling
I have a large set of data for 37 different clinical units (all oncology) in their respective 37 hospitals. There are two specific outcome variables that I need to analyse:
First, drug usage for ...
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Bayesian model averaging in R
I have a logistic model that I've built with the nls function in R. I want to use Bayesian model averaging for variable selection, but I can't find a package for ...
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Can logistic regression's predicted probability be interpreted as the confidence in the classification
Can we interpret posterior probability obtained from a classifier that outputs a predicted class value and a probability (for example, logistic regression or Naive Bayes) as some kind of a confidence ...
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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
...
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Is there any criterion about choosing reference factor in multinomial logistic regression?
I have a dependent variable that includes four categories. I also have four continuous independent variables. The 3rd category covers the largest group in the sample. Is it important to choose the ...
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How do I handle categorical dependent variables with low level percentages in multinomial logistic regression?
I have a categorical dependent variable that involves four clusters of positions. In descriptive analysis, I noticed that first cluster covered about 5% of the participants, second 6%, third 60%, and ...
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Survey Weighted Random Effects Logit Model in R
I am trying to predict a binary outcome with a model that includes a random effect using survey data. I've included a description of the sampling design below, so feel free to comment on my survey ...
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How to handle missing data in a logistic regression using SPSS?
I have a data-set of genetic variants which I'm trying to use as predictors for a simple phenotype, and for starters I use a binary logistic regression in SPSS. I have around 900 individuals, and for ...
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Alternatives to multinomial logistic regression
I have been using a multinomial logistic regression to examine the correlates of school choice. There are three possibilities for the dependent variable: government school, private school, and NGO (...
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R regression output - Factors vs numeric variables
Let's say I have the following logistic regression models:
...
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Re-parameterization of an asymmetric s-shaped function
Is anyone aware of a re-parameterization of any asymmetric s-shaped function (like, but not necessarily the 5 parameter logistic curve), where one of the parameters is the first inflection point of ...
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Predicted Probabilities for Logit Models
Last month I asked this question here.
After thinking about it recently, I was wondering if it makes sense to think about logit probabilities in that regards. Since the predictor of a coefficient ...
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Checking whether or not a variable has impact
For a statistics assignment, I've been given a data set (regarding drug prevention) and a few questions. One of the questions is to check whether or not the choice of treatment, treatment A or ...
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To aggregate and lose resolution OR not to aggregate and suffer with correlated binary data?
I have data from an experiment in which each participant provides a binary response to each presented stimulus, which is either correct (1) or incorrect (0).
There are 4 different stimulus types, ...
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Resources for developing prognostic index-scores
I am looking for online resources or books explaining how to develop prognostic indexes-scores step by step. I am mainly wondering about model validation and transformation of regression coefficients ...
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Model selection and model performance in logistic regression
I have a question about model selection and model performance in logistic regression. I have three models that are based on three different hypotheses. The first two models (lets name them z and x) ...
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