Questions tagged [clogit]
"clogit" is conditional (fixed-effects) logistic regression. It is also the command in R and Stata. The model is used for matched data, longitudinal data, panel data or repeated measures, with an individual intercept for each cluster (or subject).
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How does conditional logit deal with binary predictors in choice sets of three or more alternatives?
I am interested in clogit, not multinomial logit, and the overall effect of the predictor on the choice of n alternatives that can only be identified by their attributes (i.e., the choice sets are ...
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Panel Data logistic regression
I am working with a panel dataset that describes company code as an id variable and fiscal year as a time variable (1500 firms from 2013-2022). The dependent variable is binary. First I checked for ...
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Conditional Logit Model - Utility Structural Estimation - Meta Analysis
I am performing a structural estimation of an utility function across several databases (from distinct articles) using McFadden (2001) framework (see reference).
Each article's database includes N ...
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Clogit and no variation in strata
Suppose that I want to identify a causal effect with panel data. The dependent variable is dichotomous so I use a conditional logit with survival::clogit in R, with ...
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Retrospective cohort study with case:control matching 1:5. Is clogit really appropriate?
I study school grades in children with brain tumors (=cases), using databases.
Every case in the database has five healthy controls, matched on sex, birth year and residency. The hypothesis is that ...
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How to identify influential observations in a conditional logistic regression (clogit) model in R?
I have fitted a conditional logistic regression model using the clogit() function from the survival package in R, and I would like to identify the influential observations in my dataset. I have tried ...
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Can I specify a random intercept in a conditional logit model?
In conditional logit models, global intercepts cannot be estimated as they do not influence the conditional probability of a positive outcome within groups. I understand the intercept term gets ...
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Can I use a conditional logit for fixed effects (Chamberlain, 1980) if my assumptions are that the errors are normally distributed?
Consider that we have a dichotomous variable $D_{i,t}$ that takes the value of 1 if $Y_{i,t}\geq 0$ and 0 otherwise. And $Y_{i,t}$ is a latent variable defined by:
$Y_{i,t} = \eta_{i} + \sum\limits_{k\...
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Is there a statistical software package for the generalized conditional/multinomial logit model?
I have a discrete choice model of moving from one state to the other, so alternatives=states. I have case-specific variables such as income, race, and gender. In addition, I have moving distance ...
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Mixed effects versus conditional models for paired analyses
In this CV post I address briefly models for binary dependent data and how they might be used in a paired analysis.
Stratification McNemar Test in R
It occurred to me: I hadn't previously considered ...
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Does the coefficient from regressing a binary variable on a binary outcome only show the effect of when that binary variable is true?
I have a conditional fixed effects logistic regression of parental health shocks (0 if no shock, 1 if health shock) and clinically problematic child development (0 if no development problems in the ...
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Finding best conditional logistic regression model with unbalanced strata
I am interested in fitting the best possible model for the case of conditional logistic regression where the strata are unbalanced. Although I have not seen it specified, but I understand that there ...
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Unusual distribution of predictors in conditional logistic regression
I'm using conditional logistic regression to model the case-control status of a disease with measurements of certain blood compounds as the main predictors of interest. The objective is to find those ...
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Conditional logit or multinomial logit?
I have the following problem I need to use a discrete choice model to determine the time values (VOT) of 3 transport alternatives (car, bus and train). Looking at the literature of the discrete choice ...
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NA coefficients produced by clogit model
I am trying to run a conditional logistic regression using clogit() from the survival package. The binary response variable is ...
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Using Random Forests for modeling discrete choice problems
I am trying to model a discrete choice scenario in which (i) the explanatory variables are both individual- and alternative-specific, and (ii) the number of alternatives varies between individuals. ...
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MLE for the conditional logit model seems to have awful precision?
I'm simulating the data underlying a conditional logit model then doing my own MLE estimation using optim. However, even with an unreasonably large amount of data, ...
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From Discrete choice to Conjoint utilities
I'm having trouble figuring out how to correctly calculate conjoint part-worth-utility from a discrete choice experiment.
I have recently run a pilot study to analyse in R where I used the packages “...
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Bootstrap analysis from a conditional logistic regression
How can I perform a bootstrap analysis from a conditional logistic regression? The model has been built using the clogit function (...
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Error with clogit function in R
I am using the clogit function for the matched data with the disease-outcome and categorical predictor. However R returns message "X matrix deemed to be singular;"
I saw posts where similar ...
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Using categorical variable in Conditional Logistic Regression
I have a set of data with lots of events and I want to try and predict the outcome of the event. I have built a basic conditional logistic regression model but I want to add categorical variables ...
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Conditional Logit in a Panel Data setting with varying alternatives over waves
I am working on a panel data setting and this data is on cigarette smoking behavior of individuals.
I am specifically focusing on two variables - the brand name of the cigarette that the individual ...
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Is there any implication of a large log-likelihood value?
I have estimated a discrete choice model using the MLE procedure and got a very large log-likelihood value (log-likelihood: -236018.2). Is there any implication to the result?
[edit]
I have 4300 ...
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predict functions after clogit in R using survival package
I have difficulties understanding the different types of prediction after running survival::clogit in R. I do not think this is due to author's fault, but mainly ...
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LOGIT Regression with multiple fixed effects - STATA
For my thesis I am using as dependent variable the fraction of cash as part of the total price offered by the bidder. So, it's a fractional response that lies between [0,1]. I am not sure which ...
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How does clogit() (in R) handle incomplete strata?
I am running conditional logistic regression in R using clogit(). I have 314 different strata with 1 case and 1 control in each stratum (628 observations in total). ...
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Clogit wtp interpretation
I have performed a clogit with the package survival in R. The aim the work was to estimate the willingness to pay from a discrete choice model. The choice set was composed of 4 attributes, 3 of them ...
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matched cohort with 1:n pairs - correct stratified logistic model
In this hypothetical example we have access to a database. In it cases are people with children and controls are those without kids. We want to measure the association between having children and Lung ...
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How to determine variable type for a multinomial conditional logit model?
To give some background I am working to replicate a study using R where a multinomial conditional logit model was used to estimate the likelihood a college football recruit would attend a specific ...
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What is the difference between conditional logit fixed effect model and logit model?
I have a binary dependent variable and about 10 covariates. My dependent variable is whether a child under 5 years of age has ARI or not. I am using a DHS survey for data. Most other papers use simple ...
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Utility partworths from dicrete choice experiments
Is it possible to estimate utility partworths from a discrete choice experiment (DCE)?
For example, if you construct a DCE using the R package support.CEs and ...
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How do I model a conditional logistic model with varying choice set in R
I have a dataset, where individuals ( no repetition of individuals in the data) face different choice sets. I wanted to model the individuals choice using the mlogit function in R. All the examples on ...
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What is the best way to select variables for clogit model?
I am doing clogit model (clogit of survival package) with around 150 independent variables which are highly correlated. I have to select the combinations of the variables so that the model will be the ...
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Which is the best criterion for comparing two conditional logit regressions with different variables?
Suppose we have two conditional logit models as below:
Model-1: clogit(win~x1+x2+x3+x4+x5+strata(stratum))
Model-2: clogit(win~x6+x7+x8+strata(stratum))
I am ...
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interaction term in conditional logistic regression
I would like to do a gene x environment interaction analysis in a matched (1-1) case control samples. I referred all related previous publications and in most of the papers authors used either STATA ...
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Conditional logistic regression or GEE in PS matched study
My situation:
In a cohort study, I'm trying to find the correlation between outcome & Tx (Arm A vs Arm B). However, baseline covariates are unbalance between different treatment groups. Hence, ...
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Results from logit model using BIOGEME unexpected
I am using BIOGEME to estimate the discrete choice model (choice is made among four alternative routes). I am having hard time with modeling using BIOGEME.
I have dataset in the following format:
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How do we calculate the path size (PS) for Path Size Logit Model?
I am using Multinomial Logit model for the discrete choice analysis, in which user chooses a route among other available paths. This is intended to determine the utility of those routes. As these ...
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clogit in R: original variable or demeaned?
Conditional logistic regression is a fixed effects model. If you're modeling the dependent variable $y$, a glm fixed effect model doesn't actually model $y$. Instead, the glm fixed effect models ...
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Can you have a conditional logit without fixed effects or a simple logit with conditional probabilities?
We have a set of agents that must choose one and only one alternative out of a large number of them (max # of alternatives = 120). Agents take the decision several times, without replacement of the ...
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Do probabilities need to sum to 1 in a choice model? [closed]
We're create a discrete choice model, in which there are more than two alternative choices. There are some options for this, such as the multinomial logit and the conditional logit.. We started with ...
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Feasible Multinomial Logit with large number of fixed effects
Is there a way to run something similar to a multinomial logit model with a large number of fixed effects that converges in a reasonable amount of time (I am using Stata)?
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Interpreting Odds Ratios for Natural Log transformed Variables
For those who are using Stata the following command clogit Y X,or would produce the odds ratio from the Conditional logistic regression which is the change in the ...
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Interpretation of clogit coefficients (Survival package in R)
Still very very new to R! I've run a conjoint (choice) experiment that uses the function clogit. Output as follows: (this model has been obtained through stepwise methods)
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Case-crossover method with conditional logistic regression for poisson model generated data
I would like to run a semi-symmetric bi-directional case-crossover method on some generated data using conditional logistic regression.
I generated data from Poisson distribution Poiss(lambda) with
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Conditional FE Binomial Logit Models (Stata)
I have individual panel-level data and am using conditional binomial fe logit regressions to estimate the effect of minimum wage on Employment.
1) When I try to include year dummies most of them are ...
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Conditional Logistic Regression, Rare Events and R
I have a panel data set organized around 35 provincial units, with 110 binary "positive" outcomes in the dependent variable. This is for about 2600 observations in that data set. I have a couple ...
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How to conduct a multilevel (hierarchical) binary logistic regression (in SPSS, R, or other software)?
I have a model with occurrence of a disease represented by a binary dependent variable (DV) and 8 independent variables (IVs) at different levels. I need to create a multi-level model, in which the ...
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Relationship between McNemar's test and conditional logistic regression
I am interested in the modeling of binary response data in paired observations. We aim to make inference about the effectiveness of a pre-post intervention in a group, potentially adjusting for ...
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Less significant findings using conditional logistic regression
I used regular logistic regression on my dataset and got a few significant hits. However, since the data is 1:1 case-control matched data I decided to try using conditional logistic regression (...
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