# Tagged Questions

Count data are non-negative integers representing whole amounts. When such data are the dependent variable in a regression, Poisson or negative binomial regression may be appropriate methods. One common problem is "zero-inflation" (where the proportion of zero values is greater than predicted by a ...

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### How to perform regression on a nominal variable using many binary explanatory variables?

I have a dataset: Response: categorical, 9 levels. 23 predictors: binary, with many 0's. Number of samples: 64. I'm interested to know the dependence of (each level of) the response on predictors. ...
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### Hausman-Newey test for serial correlation in Poisson with Fixed Effects

The article from Hausman, Hall, and Griliches (1984) "Econometric Models for Count Data with an Application to the Patents-R&D Relationship" has become the canonical example for conditional MLE of ...
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### Robust test for time series count data

I'm going to analyse suicide rates for a time series and I'd like to use robust tests but I don't know which would be a good one. My purpose is to compare the variation of the suicides rates trough ...
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### How to fit a simple count time series INAR(1) model in R

I am trying to perform a simple time series analysis with count time series data. My data is a sequence of small integer values like 0,1,2 and 3. I learned from various sources that INAR model would ...
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### Predicting count data with random forest

Can a Random Forest be trained to appropriately predict count data? How would this proceed? I have quite a extensive range of values so classification doesn't really make sense. If I would use ...
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### Is splitting one hurdle model in two GLM/GAM models a valid approach?

I came across several publications dealing with overdispersed zero-inflated count data that "simply" modelled presence absence in one model and then postive counts in a second model. This led to two ...
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### Count data forecasting/prediction

I would like to know if the normal forecasting methods apply for count data, in specific a dataset that contains several zeros? I have data set that counts the usage of a service on an hourly basis, ...
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### Non-integer dependent variable in negative binomial models

I have non-nested count data that I've interpolated from one area to another based on the proportion of the area that lays in each. This is ZIP codes to counties, so most nest cleanly, with a few ...
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### Why is Poisson regression different with glmer and gamlss?

I have a set of count data that seems to fit "Poisson" = not overdispersed, alpha = 0. The problem is, I get different results using gamlss vs ...
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### Is a g-test appropriate for count data?

I am analyzing an forest ecology experiment where we counted the number of trees in 5 pairs of plots in a forest. One member of each pair was fenced several years ago to exclude deer (exclusion ...
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### Best way to find non-randomness regions in these or similar count data?

Let say I have data in a shape: [0,0,0,0,1,0,0,0,1,1,0,0,0,0,0,0,0,0,1,0,0,2,0,0,0,....] - so mainly zeros.... However I know how long is my 'signal' and how many counts are they. Is it possible ...
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### Finding underlying distribution of proportion data

I have a large dataset of count data --- count of positive cases and total number of cases distributed by distance (in meters). The empirical distribution of proportions and beginning of data are ...
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### Assessing similarities in “call repertoire” for animal vocalizations

I have count data for number of call types over an interval of time for multiple animals. What I want is (1) a summary of association between call types (i.e., if X1 is large, X2 is small) and (2) a ...
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### Underdispersed count data and factor analysis

I am working with count data from a psychological experiment. Data are from several subtests, i.e. scores on these tests. The way these scores are generated is clearly not Gaussian (not only because ...
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### CMH-test, multiple contingency tables, unpaired entries

I have frequency data for 9 populations, divided into two groups, one of five populations and one of four. I am interested in whether these two groups are different. A classic way to analyse such ...
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### For count data from a survey, do variance corrections for survey design imply that the Poisson distribution will not accurately model the counts?

I have categorical count data that comes from a complex survey. Each unit of analysis in the survey (household, individual, etc.) is put into one and only category per dimension, ranging from 2 to 20 ...
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### GLM experimental design issues for count data in landscape experiment

I am analyzing bird count data from surveys conducted each week (from Nov-April, when bird foraging most active near breeding cycle) for 6 years in 9 large experimental plots that are split amongst 3 ...
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### Am I looking at count, ordinal, or continuous data? Using a self-report questionnaire of depression

I am using the PHQ-9, a measure of depression. Here is a link to it: http://www.waterloowellingtondiabetes.ca/usercontent/documents/PHQ9PatientHealthQuestionnaireforDepression.pdf I am wondering ...
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### Multiple categorical Variables and Multiple Hierarchical Counts- how to infer the effects?

I have the following categorical/count data : ...
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### How do I model monthly count data (the number of lumbar fusion surgeries)?

I have the following data: Month-year number of people with back/neck problem number of people using surgery (lumbar fusion) as a treatment The goal is to compute usage rate of surgery (...
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### What is the correct way of estimating the proportion of individuals in a population from a count of their individual parts?

My original question was going to be : How do you estimate the proportion of species in a population from count data of their individual body parts, provided that you can identify each part as ...
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### Combine / analyse different exposure variables in count data model

The outcome $y$ in my dataset is count data. There are three possible exposure variables $e_1, e_2, e_3$ conceivable. These exposure variables are mutually exclusive, i.e. refer to different physical ...
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### Sample comparison with unknown missingness or deflation

I'm sorry if my terminology is wrong, I'm making it up. I have hundreds of objects counted simultaneously in two treatments, each measured three times (not in pairs). e.g.: ...
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### Help with R Zeroinfl model

I am carrying out a zero-inflated negative binomial GLM on some insect count data in R. My problem is how to get R to read my species data as one stacked column so as to preserve the zero inflation. ...
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### Differentially “expressed” features

When any person gets a dataset of counts for two groups (metagenomics or digital gene expression), the first thing they do is to go and find features that differ significantly between the two groups, ...
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### Combining the Counts and P-Values

I have experimental and computational data for n genes in data matrix. The rows are the genes and columns are its values. Now, the data is from two sources: Computational Prediction Results in form ...
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### determining drivers of loss rate change between two time periods (binomial regression)

I've read through the R Book and I think is the closest I've come to the problem. I have two time periods - say TEST1 and TEST2 where I have aggregated samples of data of how many 'animals' were lost ...
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### Getting started with VGAM::vglm

Trying to fit a zero-inflated Poisson model, I have trouble to understand the parameters to the vglm function in VGAM. As an ...
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### How to rescale multiple count variables of varying magnitudes to best train a classifier?

I have several features that are count data, but varying in magnitude, and I would like to scale them so that I can best train my classifier. These features are not normally distributed, so I want to ...
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### Comparison of symptom profiles: binomial GLM? (SPSS, R)

I have nine depression symptoms in a sample of $n=2000$; symptoms are dichotomized (0= not present, 1= present) and can thus be used as counts. I want to test whether the symptoms differ from each ...
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### Is discretization still the only way to deal with continuous and count variables in data mining association algorithms?

I have recently read a book chapter of data quality in which the author is against turning continuous variables in groups. While I agree with some of his arguments, I was not be able to find a way to ...
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### Is it possible to Reduce/Correct Bias through EM algorithm?

I am dealing with few overdispersed count models and using mixed Poisson distributions to deal with overdispsered data. I've used MLE technique to estimate the paramters, however ML estimates are ...
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### ZIP converges but ZINB does not. Should I drop this model?

Background: I am building a count data model with an abundancy of zeros. More precesely, I am trying to estimate the number of competitors that will enter a certain market. 70% of my data consists ...
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### What statistical test should I use to compare counts across months?

For a project, I'm trying to compare counts of fish caught per month and get statistical significance. I.e. In May I caught 300 fish, In June I caught 90 fish and in July I caught 90 fish again. ...