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 ...

learn more… | top users | synonyms

2
votes
0answers
15 views

Using Resampling to understand a large table

I have a data set that is very large. The attributes (columns) are several thousand. Some are sparse others are not. Some are ordinal, others interval, nominal or ratio. The row size is 10s of ...
2
votes
0answers
19 views

Evaluate deviation from negative binomial model

I'm trying to figure out how to determine to what extent a sample deviates from a negative binomial model fitted to a larger population. As an example, I generated counts of doctor visits for a ...
2
votes
0answers
25 views

Standardizing count variables in panel data with overdispersion - R or Stata

I'm running a regression where the dependent (response) variable is a highly dispersed (slightly zero-inflated) count and the explanatory (independent or predictor) variables are continuous, counts as ...
2
votes
1answer
98 views

GLM for count data

I ran an experiment with an eye tracker and my data frame has this look: ...
1
vote
0answers
20 views

Back Transforming Rates in Poisson GLM with Box and Cox Transformation

Suppose I have fitted a Poisson GLM to model rates as follows: > fit.1=glm(response~X1+X2+ offset(log(population)),family=poisson,data=...) I can get the ...
0
votes
0answers
16 views

Assessing the accuracy of prediction (count data with few values)

I am using three different models (NB2, Poisson, hurdle) to construct a prediction function for the count data with values varying from 0 to 7 (77,93%; 15,91%; 4,15%; 1,33%; 0,51%; 0,12%; 0,04%; ...
2
votes
1answer
84 views

Data transformation for count data with many zeros

I have a count dataset that contains many zeros and a discrete variable that contains many zeros as well. I would like to see graphically which kind of correlation exists between these two variables. ...
1
vote
1answer
29 views

Correlations in count data

I have two count data variables X and Y that contain many zero values (90% in X, 60% in Y). I would like to check if a correlation exists between these variables, but I'm not sure how to proceed due ...
0
votes
0answers
12 views

Confidence interval for fit to poisson count data, for beginner

I have the following graph, which I then normalise and attempt to fit to. The data is a histogram of counts at a given time. The fit then looks like: The issue is that the parameters ...
0
votes
0answers
18 views

Showing count data can be dichotomized without losing too much information

I am working with a set of data that has accident counts by year from taxi drivers. R code: no.accident <- c(16003,2355,4433,18823) one.accident <- c(172, 26, 232, 9) ...
2
votes
0answers
21 views

Error bar for Poisson count data

I have a set of data, counts versus time. The whole data looks like this Here is a sample ...
0
votes
0answers
72 views

How to guess a curve distribution from count data

I have a sample composed by 2500 count data values. I've plotted in R the corresponding histogram and ecdf. I've run the One-Sample Kolmogorov-Smirnov test to check if the distribution is either ...
0
votes
0answers
10 views

Additive Index: Count data or multinomial?

I would like to use an additive index, validated by Mokken analysis, as a dependent variable in a logistic regression model for categorical dependent variables. The index consists of adding values ...
2
votes
0answers
73 views

Non-parametric estimators for time-varying binomial proportion

I have a bunch of count data associated with time intervals (potentially overlapping and of variable lengths), say $(s_i, t_i, n_i, N_i)$ where $N_i$ is a count of the total number of events ...
1
vote
0answers
15 views

Interpretation of Count Models Based on Weibull Interarrival Times?

This question is an extension of this question, but more specific. This paper E. Bradlow et al is a Weibull counting model which I am using to estimate how many failures will happen between ...
1
vote
0answers
21 views

Fitting Mixture Distribution of Poisson and Negative Binomial (Delaporte Distribution)

I am trying to fit a model to some simulated data. The idea is to use ML-Estimation. However, I am totally lost. I have a dependent variable which is a sum of two (unknown) variables. The first part ...
1
vote
0answers
23 views

Exp(B) value outside 95% Wald Confidence Interval

I ran a negative binomial regression on some count data using SPSS. The intercept had an Exp(B) value below the lower limit of the 95% Wald Confidence Interval. I've never seen this happen before ...
5
votes
3answers
205 views

Regression model for proportion or count when counts of outcome and total events are often zero

I need help thinking about and identifying the kind of regression analysis that would be appropriate for this problem. Nothing I've discovered so far seems quite right. Referrals to articles or ...
2
votes
0answers
64 views

Suitable method for modelling (underdispersed?) count data with lots of zeros and long tail

I have a small data set of counts of bees. I tried a simple Poisson model without random effects but it was very overdispersed (3.95). When I fit a GLMM with random effects (using glmer in lme4) it ...
1
vote
0answers
151 views

Trouble finding good model fit for count data with mixed effects - ZINB or something else?

I have a very small data set on solitary bee abundance that I am having trouble analysing. It’s count data, and almost all the counts are in one treatment with most of the zeroes in the other ...
0
votes
0answers
29 views

Is there a way to statistically differentiate parametric and count data?

I'm wondering whether there are any statistical properties that should differentiate count data and parametric data. In other words, is there an aspect of my data that I can analyze, or a test I can ...
3
votes
1answer
83 views

How do you estimate the predicted probability of an integer value from a negative binomial regression equation?

I'm trying to estimate the predicted probabilities of an observation being a particular integer, $y$, after a negative binomial regression model. Long's Regression models for categorical and limited ...
0
votes
0answers
41 views

Using QAICc with Poisson, or AIC with Poisson lognormal, in information theoretic approach?

I am trying to use an IT approach to analyse some ecological data. I have a mixed model with nested random effects (I'm using glmer in package lme4 in R). I initially fit the model with a Poisson ...
4
votes
0answers
38 views

Comparing 2 independent counts of the same data

I am looking for an appropriate statistical method to test my hypothesis that there is no significant difference between counts conducted by 2 individuals of the same data. The data is as follows: I ...
0
votes
0answers
26 views

Calculating significance for fold-enrichment for proportions

Right, so I've got data in the following format... ...
0
votes
0answers
32 views

Count Data Modelling

I am using count models like Poisson, Negative Binomial [NB], zero-inflated NB [ZINB] on data having high proportion of zeros. NB fits much better than the Poisson counterpart and interestingly it ...
3
votes
0answers
41 views

Annual time series count data where the dependent variable is a count averaging 3,000 and no zeros

I need your assistance on time series count data. I got some annual time series data I want to run, however the dependent variable is a count (number of deaths) while the independent variables are ...
1
vote
1answer
86 views

Comparing Counts Between Two Independent Groups

I have 2 groups of patients and I'm looking at what percentage were discharged from the hospital at different time points after surgery. ...
2
votes
2answers
109 views

Is my Poisson regression correct?

Here are my data: ...
2
votes
1answer
108 views

Poisson or binomial regression?

I have a binary response variable (it is a presence/absence variable) and a ordinal discrete predictor: ...
0
votes
1answer
48 views

Count data with continuous variables

Let's assume one has looked at the occurence of a plant species at different altitude, different temperature and environment. Here are its data: ...
0
votes
0answers
15 views

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, ...
0
votes
1answer
69 views

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 suicide rates through ...
2
votes
0answers
93 views

Log-linear or poisson model with R [closed]

I have a data.frame (myData) with 6 variables which are: ...
1
vote
0answers
56 views

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 ...
0
votes
1answer
42 views

Comparing category distributions

I have categorical count data (for categories C1 to C3, but potentially several more categories) for two datasets: ...
0
votes
0answers
28 views

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 ...
5
votes
1answer
78 views

How to compare rates of occurence in consecutive time series count data?

My data consists of occurrences of words in time windows. E.g.: Day; Word; Frequency 1; "dog"; 45 1; "cat"; 2 ... 2; "dog"; 90 2; "cat"; 4 ... I would like to ...
2
votes
1answer
66 views

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 ...
4
votes
1answer
188 views

Enormous SEs in zero-inflated negative binomial regression

I have overdispersed count data where the outcome is events (occurrence of a rare disease) and the covariate of interest is season. The unit of analysis is the number of events occurring in a ...
0
votes
0answers
36 views

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 ...
4
votes
1answer
130 views

Time series dynamic poisson regression

I have a time series count data by customers that I would like to regress on past months items (count) sold and promotional effects (current and past). Below is an example, and the dataset has one ...
0
votes
0answers
48 views

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 ...
1
vote
1answer
53 views

Count regression model Results

I am trying to draw some conclusions about the fitting of one model, but after looking at some examples in the internet I just can't get a hold of it, the interpretation of the results I mean. Since ...
0
votes
1answer
277 views

Alternatives to ratios of counts if denominators can be zero

This is probably a really dumb question but I can't find the answer anywhere. I have been given a bunch of data and asked to calculate proportions between two variables. The variables are both counts ...
0
votes
1answer
176 views

Checking for multicollinearity in a negative binomial regression model

I'm a beginner and have this question: In a negative binomial regression analysis, is it possible to check if there is multicollinearity? I'm trying to introduce some moderating effects (e.g. ...
1
vote
0answers
20 views

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 ...
0
votes
1answer
172 views

Count data as an independent variable in OLS- using a dummy variable+ the variable linearly to account for skewness

I am using OLS to model the relationship between amount of foreign aid (dependent variable, logged) and media coverage (number of newspaper articles, count variable). I assume a linear relationship ...
2
votes
0answers
71 views

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, ...
0
votes
0answers
26 views

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 ...