# Tagged Questions

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

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### I want to find contributions of each independent variables

I would like to get contributions of independent variables (factors driving sales) in absolute dollar values. The log linear equation looks like this: ln(sales)=b1*ln(baseline)+b2*weather +b3*holiday +...
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### Log linear analysis with weights

I am trying to conduct a log linear analysis using deer count data from Heisey (1985) and used as an example in Resource selection by animals by Manly (2002). They use a program named GLIM (...
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### loglinear analysis, assumptions met?

We've data from a large ongoing project at a big science museum. We are showing people plates of food where we vary the plate shape (round or square; 0,1), food arrangement (polygonal or vertical ...
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### Sample size log linear analysis?

Is there a rule of thumb for the sample size for a log linear analysis? For example, would it be inappropriate to use this analysis for a sample size of 50 with 3 predictors?
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### $\chi^2$ of multidimensional data

I want to test if two observations of nominal data accord to the same distribution. I am using the chi squared statistics to perform a chi squared homogeneity test and normalize the result with Cramer'...
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### What's the right interpretation for parameter estimates in loglinear modelling?

I'm doing a loglinear analysis of the following data. Male is coded as 1, Female as 2. Senior workers are coded as 1, middle level as 2, and shopfloor as 3. A is coded as 1 and is the most ...
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### Interpreting dummy variable in semi-log model

There are numerous theories on how to interpret the coefficients of dummy variables in a semi-log model but I still am not sure about it. Do we multiply the coefficient by 100 to get the change like ...
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### Advice for test on categorical variables

I am working with two variables - variable 'A' is an independent categorical variable and has three levels 'a' 'b' and 'c'; variable 'B' is continuous response variable data I have classified into ...
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### Using contingency tables for testing multiple dependencies

I know that I can determine the correlation / association / dependency between two variables (X= smoker, and Y=cancer) using chi-squared with a 2x2 contingency table: ...
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### How do I find the odds ratio using the output of a loglinear model?

This was a homework problem from Agresti (7.2) that I didn't get, even after looking at my class' solutions. Help? So we are given the output of a loglinear regression ($λ_{ij}^{XY}$). The output is: ...
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### Regression Model for Binary Matched or Paired Contingency Table Results

This is a follow-up question on a prior thread about the same setup as follows: We have two "Methods" ("A" and "B") to diagnose a medical condition. We are not trying to determine which one is better ...
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### Correlated Proportions shown in a Mosaic Plot. What is the fitted model that generates residuals?

I have a 2-by-2 table of correlated proportions where I am plotting the positivity of two diagnostic methods applied on a sample of 216 individuals: ...
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### Comparing Proportion of Positive Tests

A condition or disease (D) is measured using two different methods (A and B) in a sample of 1,000 individuals from a population. Using method A, the percentage of positive cases is 25%, whereas method ...
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### Antilog of a semilog regression model with dummy variables

I have a semi-log regression model, with two continuous predictors, two categorical predictors (0 or 1 dummy variables) and a non-zero intercept. The response variable is log10 transformed, none of ...
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### Selecting the best subset of features in binary logistic regression [duplicate]

I am using a binary logistic regression (a type of probabilistic statistical classification model, is used to predict a likelihood of belonging to a class (True, False)). I have 4 features and I want ...
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### Fitting a heteroscedastic generalized linear model for binomial responses

I have data from the following experimental design: my observations are counts of the numbers of successes (K) out of corresponding number of trials (...
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### Linear regression with log dependent variable

I have the following regression: $log(Y) = \alpha + \beta X + \epsilon$ with $E[\epsilon] = 0$ and $var(\epsilon) = \sigma^2$. There is no assumption on the distribution of the errors $\epsilon$. In ...
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### Type of inference to use with log-linear Poisson glm on contingency table frequency counts

I was doing some log-linear models to test for interactions/associations in multiway contingency tables (based on the tutorial here, http://ww2.coastal.edu/kingw/statistics/R-tutorials/loglin.html). I ...
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### Log Linear Models: Interpretation when None Fit

This is question 9.6 from Categorical Data Analysis by Alan Agresti (Wiley, 2013). The question asks us to find a Log Linear with the best fit for a 2x2x2 contingency table. The following are the ...
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### Exploring dependencies between variables in log-linear models

Hi there I'm using R to perform some multivariate data analysis on health data. I'm currently using the glm() function with <...