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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1answer
97 views
Overdispersion parameter
I am modelling a zero-truncated process with a count model, and am trying to determine whether the data are overdispersed. The Poisson distribution has a variance equal to its mean,
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3
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1answer
612 views
Zero-inflated negative binomial mixed-effects model in R
Is there such a package that provides for zero-inflated negative binomial mixed-effects model estimation in R?
By that I mean:
Zero-inflation where you can specify the binomial model for zero ...
2
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1answer
463 views
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. ...
1
vote
1answer
51 views
Fitting a Poisson distribution from missing observations
I am interested in fitting a Poisson/negative binomial distribution to estimate the number of times a phenomenon happens within a period, let's just say 10 years. I can count the events from monthly ...
4
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0answers
119 views
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 ...
3
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0answers
129 views
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 ...
2
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0answers
17 views
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 ...
2
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0answers
80 views
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 ...
2
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0answers
123 views
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 ...
2
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0answers
61 views
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 ...
1
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0answers
17 views
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 ...
1
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0answers
29 views
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 ...
1
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0answers
71 views
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 ...
1
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0answers
91 views
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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0answers
73 views
Multiple categorical Variables and Multiple Hierarchical Counts- how to infer the effects?
I have the following categorical/count data :
...
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0answers
143 views
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 (...
1
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0answers
111 views
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 ...
1
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0answers
84 views
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 ...
1
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0answers
46 views
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.:
...
1
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0answers
220 views
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. ...
0
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0answers
16 views
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 ...
0
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0answers
19 views
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 ...
0
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0answers
53 views
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 ...
0
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0answers
77 views
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.
...
0
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0answers
55 views
singularity of the Poisson counting process for non-statistician
I would like to explain to non-statisticians the singularity of the Poisson counting process over others (if possible, in a simple sentence). Simply translating in non-mathematical terms its formal ...
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0answers
96 views
Analyzing online sales where data are only produced when the sales is made
I am trying to model data on the number of online sales are made within a fixed sale period of 3 days. Data are generated only when the sale is made. I think for this kind of data I will be using a ...
