Tagged Questions

2
votes
0answers
43 views

Variable selection / Dataset reduction for large datasets (in R)

I'm working on a behavoural scorecard modelling exercise, and many of the decisions taken to date have been based on the experience of a consulting credit analyst (whose experience software-wise is ...
0
votes
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
30 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 ...
2
votes
3answers
130 views

Pros/Cons of recoding ordinal/nominal variables to target mean for logistic regression?

Say I have an independent variable with the following relationship to the binary dependent variable, DV: ...
2
votes
0answers
126 views

Is the Mundlak fixed effects procedure applicable for logistic regression with dummies?

I have a dataset with 8000 clusters and 4 million observations. Unfortunately my statistical software, Stata, runs rather slowly when using its panel data function for logistic regression: ...
0
votes
1answer
93 views

Logistic regression with categorical data

I'm trying to apply logistic regression to the data with binary predictor. But some of my variables are numerical and some are categorical. If I just do this in R I get the model where for every ...
1
vote
2answers
347 views

Multinomial logistic regression vs 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? ...
3
votes
1answer
102 views

Building separate logistic regression models for each categorical variable

I am building a binary logistic regression model. I am not sure if using the variables as interactions is a better choice than building separate models for level of a categorical variable. Is there a ...
3
votes
1answer
114 views

Indicator variables and backward elimination with GLM

I am running logistic regression using glm in R on data, that has some indicator variables to it. Two of those have multiple levels and have been rewritten as ...
1
vote
0answers
80 views

How to test proportions of a Categorical response variable for a Repeated measures design with Unequal Sample Size?

I have a question about the analysis of a unequal sample size repeated measures data with categorical response variable. This experiment looks at 5 young and aged persons and for each of the ...
2
votes
2answers
491 views

Plotting logistic regression interaction (categorical) in R

Hello I have the following logistic model with a categorical variable interaction which I wish to plot in R but I am struggling to find any solutions - ...
0
votes
1answer
690 views

How do I interpret logistic regression output for categorical variables when two categories are missing?

I am using binary logistic regression; the dependent variable is 1 or 0; the independent variables are two groups: the first group includes continuous variables (...
1
vote
0answers
54 views

Model for multivariate ordered categorical data with a time-varying continuous covariate

I would like to develop a model for multivariate ordered categorical data that also allows inclusion of a time-varying continuous covariate. This is for different types of adverse events, that can ...
1
vote
1answer
127 views

Multinomial regression with categorical choice and predictos and factor analysis

I have a non-ordinal categorical dependent variable with 3 choice outcomes and 20 ordinal categorical predictors and want to do a multinomial logistic regression. However, I want to reduce the ...
0
votes
1answer
193 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 ...
0
votes
4answers
1k views

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 ...
5
votes
1answer
427 views

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 ...
5
votes
1answer
1k views

Generalized estimating equations output in SPSS

I am hoping to confirm that I have a suitable way to analyse the different proportions of people who are categorized as left lateralised on the one hand, or bilateral/right lateralised on the other in ...
2
votes
0answers
122 views

What is the effect of merging categories on logistic regression estimates?

I have a logistic regression with a number of predictors variables including a factor with, say, 5 categories. The estimates for that factor compare categories 2-5 in turn to the reference category ...
1
vote
1answer
214 views

Is it appropriate to do a multiple logistic regression where both the dependent and independent variables are binary?

Is it appropriate to do a multiple logistic regression where both the dependent and independent variables are binary? Or, can I only use simple logistic regression? What's the difference between ...
0
votes
1answer
316 views

Is there a fuzzy distinction between discrete and categorical variables?

Are there some variables where it can be difficult to assess whether they are purely categorical? For example: To assess the level of pain that a patient is in, you use a scale between 1 and 10.I ...
3
votes
1answer
540 views

How to fit Bradley–Terry–Luce model in R, without complicated formula?

The Bradley–Terry–Luce(BTL) model states that $p_{ji} = logit^{-1}(\delta_j - \delta_i)$, where $p_{ij}$ is the probability that object $j$ is judged to be "better", heavier, etc, than object $i$, ...
0
votes
1answer
1k views

Dummy variables and likert scale

So I have two related questions. I am performing a logistic regression model and want to know how to enter these variables. 1) For one survey I have questions and the responses are Yes, Don't know, ...
2
votes
1answer
923 views

Logistic regression on categorical data

I have large dataset (around 2 million records and 300 features) with a lot of missing data. Most of the independent variables are categorical (some of these variables have more than 40 valid values). ...
2
votes
2answers
1k views

Categorical variables in multinomial logistic regression end up converted into binary variables

When I run multinomial logistic regression with some of the explanatory variables as categorical, my algo (glm) turns them in binary variables, automatically. For examples if one categorical variable ...
1
vote
1answer
326 views

Coding of categorical variables in logistic regression

I have to do a binary logistic regression. I have a set of 7 independent variables. 4 of them are binary variables and the other 3 are categorical variables. The categorical variables are divided into ...
5
votes
1answer
174 views

Including day of week in a logit model

Let's say that I am putting together a logistic regression model where I am predicting something (y) based on the day of the week. However, the model needs to account for each single day. Therefore, ...
1
vote
1answer
617 views

More than one outcome (dependent) variables in ordinal logistic regression

I want to run ordinal logistic regression (OLR) in SPSS. My data include 6 predictor variable (two continuous and 4 categorical ) but my outcome variables are also 6 (categorical-likert scale). e.g my ...
1
vote
1answer
332 views

Use of further analysis on factors formed by principal component analysis in regression

I want to find out the relationship between 6 independent variable (4 categorical, 2 continuous) and 6 dependent variables (5 likert scale). As my data is categorical (likert scale) I thought of using ...
0
votes
3answers
944 views

How to handle more than one dependent variable (categorical) in logistic regression?

My data consists of 6 independent variables (continuous and categorical) and 8 dependent variables on likert scale (categorical). I want to use multinomial logistic regression to find out the ...
3
votes
1answer
571 views

Independent variables in ordinal logistic regression

One of my IV's for my ordinal logistic regression is a nominal categorical variable with 4 categories. Most examples I see for this type of logistic regression have only binary categorical variables. ...
3
votes
2answers
969 views

Which link function for a regression when Y is continuous between 0 and 1?

I've always used logistic regression when Y was categorical data 0 or 1. Now I have this dependent variable that is really a ratio/probability. That means it can be any number between 0 and 1. I ...
3
votes
2answers
2k views

Assessing the effect of adding a variable using stepwise forward logistic regression using Stata?

I'd really appreciate help using Stata to perform a manual stepwise forward logistic regression. I have 37 biologically plausible, statistically significant categorical variables linked to disease ...
6
votes
2answers
802 views

How to choose number of dummy variables when encoding several categorical variables?

I'm building a logistic regression, and two of my variables are categorical with three levels each. (Say one variable is male, female, or unknown, and the other is single, married, or unknown.) How ...
5
votes
1answer
469 views

Calculating predicted values from categorical predictors in logistic regression

Context: I am working with an ordinal logistic model and trying to interpret/present the results. The model has two continuous predictors of interests, and a mix of continuous and categorical ...
2
votes
2answers
244 views

Plugging in mean values/proportions to a logistic regression with continuous-discrete interaction

I have a logistic regression (in SAS, for reference) with continuous and categorical predictors (with reference coding), and an interaction term between one of each type (assume for now that the ...
4
votes
2answers
9k views

How to deal with not-binary categorical variables in logistic regression (SPSS)

I have to do a binary logistic regression with a lot of independent variables. Most of them are binary. Few ones are categorical with more than two possible values. Which is the best way to deal with ...
5
votes
3answers
3k views

Multiple Chi-Squared Tests

I have cross classified data in a 2 x 2 x 6 table. Let's call the dimensions response, A and ...