# Questions tagged [log-linear]

The log-linear model is a form of Poisson regression that allows for the analysis of multi-way contingency tables.

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### How Can I Interpretation in loglinear regressions with coefficients greater than 1

I run a loglinear regression and got dummy variable coefficient for education level bigger than one. It's also significant and my depend variable's log wage. How would I go about to interpret the 2.21?...
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### Correlation of categorical data to binomial response in R

I'm looking to analyze the correlation between a categorical input variable and a binomial response variable, but I'm not sure how to organize my data or if I'm planning the right analysis. Here's my ...
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### Productivity estimator

I wanted to estimate the productivity parameter in the production function. I estimated it using levinsohn and petrin (lp) method. It is a semi-parametric regression estimation. It takes raw material ...
44 views

### Mean of predicted values in a log-linear model

I run a log linear model $$\log(Y)=\alpha + \beta X + \epsilon$$ and wonder how to calculate the mean of predicted values, in the same dimension as the initial (untransformed) variable Y. I would ...
26 views

### How to interpret the results of a loglin/loglm model?

i've been working with a dataset of the following form: ...
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### Log-linear fit and parameters in case of perfectly correlated variables

Here is an example case. Take the following ´data´: ...
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### Check if dropout rates are independent for an interaction of two independent variables (one with a large amount of levels)

I am trying to analyse dropout rates in an experiment, but there are multiple issues which collide, and I don't know how to deal with them as a whole. First, find a list of those issues. Below, see a ...
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### Statsmodels - 'corrected predictors' on log-linear models?

I'm currently working through an econometrics book , and in the section about log linear models it is stated that predictions made with ...
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### Log-linear model for contingency table with no fixed count

I have table of counts of born children with four two-level factor variables (mother smoker/nonsmoker, child born dead/alive, ..). I would like to use log-linear model to understand interactions of ...
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### Help needed to Interpret ln(y) = a +b (Standardized X)

I am analysing server data and I have a scenario where I need to get the % by which Y is changed because of a unit change in X: EDIT: I am doing a Linear Regression in Python (and its other forms ...
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### Appropriate way to visualize significance in 2x3 contingency table using mosaic plot

I've checked multiple threads about handling or visualizing contingency tables, but can't find one that can help my current question. I have a 2x3 contingency table: "group" variable has 3 levels not ...
26 views

### Interpreting log-linear model for contingency table in R

I'm looking at sample data and trying to determine whether there is any association between the height of the husband and that of the wife below. I don't fully understand what the symbolic ...
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### Difference between null and saturated log-linear models

I have data from an experiment testing the number of 'cases' at each of three measurement points (0, 12, and 24 weeks). I am interested in whether the proportion of cases across these measurement ...
146 views

### Interpretation of a log-level regression in its 'level' form

Is it conventional to interpret a least-squares regression with a log-transformed dependent variable (log-linear least-squares model) in its "level" form? In other words, running a model with the ...
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### Parameters, constraints and MLE of log-linear models

I want to use log-linear models to assess the type of (in)dependence between variables in $2\times2$ and $2\times2\times2$ contingency tables. In the process of doing so I would also like to ...
124 views

### Log-linear difference-in-differences

I am estimating several linear models using a difference-in-differences (DiD) framework. The model interacts a treatment indicator (i.e., 1 for the treatment group, 0 for the control group) and a "...
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### When to use a multicategory logit model versus a loglinear model?

Do you only use the baseline-category logit model when categorical responses have more than 2 categories? How is this different than the loglinear model, which is useful when at least 2 variables in ...
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### Bivariate analysis as a basis for a subsequent analysis?

I have run across many research articles which used bivariate analysis, whose results become the basis for a subsequent analysis. For example, a Chi-squared test was used as a preliminary analysis to ...
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### Log-Linear Output Help

I ran a loglinear model with 3 variables. Internet Use (Y/N), Nervous Breakdown(Y/N), and Happiness (3 levels). I understand by two way interactions are significant, but I am getting lost trying to ...
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### logliner analysis on SPSS with more than 10 variables

I want to run logliner analysis on SPSS Statistics 25 but I have more than 10 variables.= 1 outcome variable and 11 predictors/factors. The big number of factor variables can be explained by the fact ...
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### Log-linear regression: interpretation of RSE

AIM: To really, really understand what the model outputs mean in a log-linear regression, specifically, how to interpret the residual standard error (RSE). I have read this post but it does not ...
555 views

### Confidence interval of a log-linear regression

AIM: Make a confidence interval statement on a log-linear regression I have read posts like: Interpreting Standard Deviation of Natural Log Transformed Data Lognormal Regression? But they do not ...
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### INTERPRET A REGRESSION MODEL WHEN OUTCOME VARIABLE IS LOG TRANSFORMED [duplicate]

I have used a linear model between a log-transformed outcome variable and a group of predictor variables. In this model, the dependent variable is in its log-transformed state, and the independent ...
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### Poisson log linear Regression: using either R or python

I was hoping someone can help me with this problem. I posted a similar question earlier but it's not the same. I have the following: A 2x2 matrix of structural connectivity values between brain ...