Linked Questions

3
votes
1answer
1k views

AIC/BIC for model selection between GLM and LM? [duplicate]

I've got a couple different models (poisson regression vs. OLS linear model on log-transformed DV) and trying to compare the two. They both provide reasonably good fit to the data. I have heard ...
2
votes
1answer
845 views

Non-normal variable: multiple vs poisson regression [duplicate]

If my outcome variable is count data, people often recommend using some type of poisson regression. I'm struggling to understand why this is the preferred method. Lets say for this scenario that my ...
68
votes
18answers
89k views

Statistics interview questions

I am looking for some statistics (and probability, I guess) interview questions, from the most basic through the more advanced. Answers are not necessary (although links to specific questions on this ...
35
votes
5answers
57k views

Why is Poisson regression used for count data?

I understand that for certain datasets such as voting it performs better. Why is Poisson regression used over ordinary linear regression or logistic regression? What is the mathematical motivation for ...
79
votes
1answer
92k views

How to interpret coefficients in a Poisson regression?

How can I interpret the main effects (coefficients for dummy-coded factor) in a Poisson regression? Assume the following example: ...
32
votes
3answers
75k views

How to decide which glm family to use?

I have fish density data that I am trying to compare between several different collection techniques, the data has lots of zeros, and the histogram looks vaugley appropriate for a poisson distribution ...
25
votes
6answers
15k views

Dealing with correlated regressors

In a multiple linear regression with highly correlated regressors, what is the best strategy to use? Is it a legitimate approach to add the product of all the correlated regressors?
18
votes
4answers
3k views

Why is Ordinary Least Squares performing better than Poisson regression?

I'm trying to fit a regression to explain the number of homicides in each district of a city. Although I know that my data follows a Poisson distribution, I tried to fit an OLS like this: $log(y+1) = ...
11
votes
3answers
6k views

What regression model is the most appropriate to use with count data?

I am trying to get a little into statistics, but I am stuck with something. My data are as follows: ...
7
votes
3answers
2k views

Test to know when to use GLM over Linear Regression?

Generalized Linear Models (GLMs) are more general than Linear Regression by construction. Nearly the same question was asked here: When to use GLM instead of LM?. However I'm not very satisfied of the ...
12
votes
1answer
5k views

OLS vs. Poisson GLM with identity link

My question reveals my poor understanding of Poisson regression and GLMs in general. Here's some fake data to illustrate my question: ...
8
votes
1answer
13k views

Interpreting coefficients for Poisson regression

I don't understand how to interpret the coefficient from a Poisson regression relative to the coefficient from an OLS regression. Suppose I have time series data, my left-hand side variable is number ...
7
votes
2answers
2k views

Poisson Regression : expectation vs probability for each outcome

The Poisson regression can be used to predict the expectation count. e.g: E(number of car | male = 1 & income = 40000) = 1.3 To get this, we can use the predict function in ...
3
votes
2answers
1k views

Why is linear regression results so much different from Poisson regression?

I ran both a linear regression and Poisson regression on count data (data ranges from 0-54) with two continuous predictors and the p values were very different between them. ...
2
votes
2answers
5k views

Count Data - Gaussian, poisson or quasipoisson?

So my dataset has columns Male, Female, Month and Region (East or West). And as this is a count data (number of recordings of either male or female cannot be less than 0 for any entry) I am supposed ...

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