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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Sample size determination for estimating a count

I want to estimate a simple variable: "**how many times my website is visited in 2015?". Suppose that I cannot count all visits to my website (it is expensive!), but I can count the connections on ...
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1answer
23 views

Poisson normal approximation for comparing means of count data

I'm trying to compare the values of two counts from an A/B test, $c_1$ and $c_2$. If I assume the data is Poisson distributed then the mean and variance are $\lambda$ and the standard error is $\...
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1answer
58 views

Fractional dependent variable: Why not use Poisson regression?

In many settings, we are interested in estimating a model with a fractional dependent variable. For example, Papke & Wooldridge (1996) http://faculty.smu.edu/millimet/classes/eco6375/papers/papke%...
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18 views

Conditional independent Poisson variables modelling count data

A study question I have been looking at for sometime has confused me somewhat. I have conditionally independent Poisson count observations with a hierarchical structure to the data. The format of ...
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1answer
21 views

How to operate on a count dataset (positive whole numbers with a lot of zeros) using neural networks for classification?

So i have some dataset, which is basically a count dataset. I have my own code for the classification using neural networks. Turns out that the data does not have a lot of correlation so accuracies as ...
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2answers
125 views

How to find the sweet spot

In R I have data where head(data) gives ...
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21 views

How to test the distribution of the transcripts per million (tpm) values and analyze ASE (allele specific expression) differences between haplotypes?

I have the TPM (transcripts per million) values generated for my RNAseq data. My overall goal is to identify genes that show allele specific expression differences. In the table below the TPM values (...
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0answers
13 views

Relationship between two (zero-inflated) count variables

TLDR: How can I model the relationship between two count variables that are both dependent on the same third, unobserved, continuous variable. Detail I am interested modelling the effect of an ...
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34 views

Comparing count data models?

I am trying to fit Negative binomial, Zero Inflated Negative Binomial, Negative Binomial Hurdle, and Random effects negative binomial. Here is the value of AIC for different model: Negative Binomial: ...
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1answer
33 views

Forecasting a distribution for count data

I'm working on a project to forecast the distribution of a baseball player's "At Bats per game" (a baseball statistic w/ integer domain) using a player's position in his team's batting order as a ...
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12 views

Parameter interpretation for discrete weibull regression

Please can someone provide an accessible interpretation of the parameter estimates from a discrete weibull regression model, e.g in R: ...
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1answer
23 views

Poisson regression with different exposures dependent and predictor variables

I am trying to fit a Poisson regession in R, using rates: $\ln(\mathrm{rate}_i) ~= a + bx_i + c \ln(\mathrm{old\_rate})_i$ My issue is that the predictor variable $(\mathrm{old\_rate})$ is also a ...
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1answer
23 views

Determining if points out of control - non normal distribution

I am trying to create a process in which I can identify if a process is out of control. My idea was to do something similar to 6 sigma, where when a point is outside of the mean by +-3 sigma, then ...
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1answer
31 views

Difference between logistic regression and chi-square for analysis with no covariates?

I have a binary response variable (0s and 1s), the distribution of which that I want to compare to chance. I understand I could use logistic regression or a chi-square test to do this and that these ...
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23 views

Model for count data with different exposure time (some times are terminated by death)

I am looking for most suitable model for count data in the following case: we collect number of patient's visits in a hospital for $t_i$ days ($t_i$ varies across subjects) some patients died ...
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19 views

Obtaining AICc weights after glm.nb

I am performing negative binomial regression using glm.nb() function from MASS package and calculating AICc using package "AICcmodavg". I need also to obtain the (AICc) weights using aictab() function ...
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16 views

Most appropriate test for count data

So I've performed an experiment whereby I had 12 1km transects. 6 of these were along rivers running through agricultural land and 6 through woodland. These were arranged in pairs so that each agri ...
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22 views

Count regression for a response that have a strict upper bound

I wonder what is the optimal way to conduct count regression when the response variable has a strict upper bound. For example, I would like to relate some predictors to how many lung lobes are ...
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0answers
17 views

Standard error of mean for overdispersed count data

I have count data from survey transects at several sites (typical n ~10). I am interested in whether the sample mean exceeds a threshold at [1-alpha]% confidence level (...knowing I have low power), ...
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25 views

Count data that can take only 4 values

What is a good model for estimating a regression whose count dependent variable that only has 4 values: 0, 1, 2, 3? The variable is not truncated, it is just something that can only be from 0-3. I've ...
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1answer
35 views

Searching for a good book on count data

I am seeking recommendations for a good book on count data, with clear explanations of topics like Poisson regression. The level of the book should be suitable for a graduate math and statistics ...
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14 views

Count data regression model formulation

I am working on one of the discrete probability distribution having pmf as P(x)={p^log(1+x^c)}-{p^log(1+(x+1)^c)} 0<p<1; c>0; x=0,1,2,. It fits well ...
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1answer
111 views

Normalization of count data of time periods with different length

I have count-data from two time-periods which differ in length. The event I'm counting is in both periods the same kind of event. Period 1 is 120 hours Period 2 is 48 hours At the end I have ...
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40 views

Dependent variable is count data, which method to use?

Which method should I use to analyse the relationship between count variable (absent days) and other 4 variables? Should I standardise Size variable? Please recommend some further literature/ ...
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37 views

One-sample t-test on count data

I’m working with sports performance data (ice hockey). The question I’m trying to answer is: Does the number of duels player A won in a specific match differ significantly from the mean number of ...
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26 views

Modeling count data over years through poisson regression

I have the following problem. I am trying to use the poisson regression on my data, which look like this: ...
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3answers
652 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: ...
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3 views

Validation of prediction interval for count data

I have developed a random-effects (frailty) survival model for repeated events which enables calculating individual-specific mean and prediction interval for the cumulative incidence (rate) of future ...
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16 views

Formula logic of Croston's method

In an article of Willemain et al (2014) (doi:10.1016/S0169-2070(03)00013-X) do they give an explanation of the Croston's method in which they use the following equations: How can the forecast of <...
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1answer
41 views

Measure of central tendency for periodic variable (hour of day)

I have a dataset that shows, for each group, the number of times a certain action was completed during each hour of the day. ...
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20 views

Which statistical test is most appropriate for my count data?

I did a study looking at how the number of times a specific behaviour is performed during a courtship ritual is affected by temperature treatment, while trying to control for the body size of the male ...
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1answer
90 views

Forecasting Poisson, accuracy and prediction intervals

I'm trying to forecast Poisson data, divided in groups, of 1-26 months of data, depending on the group. Of the pooled data ...
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1answer
47 views

Analysis of Categorical and Likert-Like Survey Data

I'm about to have data from intercept surveys conducted in parks. The goal of the survey is to determine which characteristics of parks users find most important to park quality (do they care a lot ...
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0answers
36 views

Selecting Link Function for Negative Binomial GLM

I'm trying to model insect abundance data with a variety of vegetation/site related covariates. Because it is count data that is over-dispersed, I've decided to use the negative binomial distribution. ...
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0answers
9 views

Modeling different rates with same offset

I'm working on my PhD and trying to analyze some data and would appreciate anybody's two cents. I'm going to trying to explain my issues with a simplified example below. Generally, I am trying to ...
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23 views

Can I sum up my count data instead of performing some repeated measures analysis?

I want to analyze establishment of plants in created gaps (plots): I have 10 treated plots, which are divided into an outer section and an inner one and I have been looking at these plots over a ...
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10 views

Poisson regression with days per week as the DV

I am estimating a poisson model (and negative binomial for comparison) with the number of days in a week that a person made a fishing trip as the dependent variable. The range of this variable is ...
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0answers
18 views

Smoothing weekly count data

I have samples of weekly count data for shoppers. The counts are based on hourly observations For example, for week 1 the hours of observation were Monday 1 PM Wednesday 4 PM Thursday 11 AM ...
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1answer
40 views

Nonparametric methods for count data?

I have data where the dependent variable are counts of an event. I am modeling the relationship between the dependent and independent variables using a negative binomial model, but I was also hoping ...
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0answers
45 views

Discretizing count data (poisson distribution)

Hi I am using next generation sequencing data (Chip-seq) for a machine learning problem. The data is represented as counts of fixed sized regions of genome (in this case 1000 bp) each 1000 bp bin ...
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21 views

Mixed effects model with missing count data

I have bird count data over a period of ten years from 15 different sites. For each site I have the month of the count, the year of the count, and the count number of birds. I need to analyse the data ...
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1answer
30 views

How to test repeated, nested, count data

I have samples from an experiment in which I have counted cells. I took 2 pictures of each kidney, photographing both kidneys of each subject. Each individual belongs to a group (infection). My ...
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1answer
20 views

Multinomial Count Models

Is it possible to model a dependent variable which is both multinomial and count? If so, how would one do so with a tool such as R? For example, suppose that my dependent variable looks like this: ...
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22 views

Comparing Two Count Variables Within-subjects

I have data where I asked participants to list 5 people that they thought fit a particular category. We then coded whether the people were men or women and counted the number of men and the number of ...
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1answer
60 views

Using Poisson GLM for visits to a historical monument - Am I using the right method?

Dependent variable - number of visitors to a historical monument by day Independent variables - Daily average temperature, relative humidity, number of tourists visiting the state by day, etc. My ...
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0answers
16 views

Iterative Maximization issue in Truncated Negative Binomial Regression in Stata

I was running truncated negative binomial regression in Stata and got a problem. During the iteration process, my results show " backed up" at the end of final iteration which means Stata could not ...
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0answers
16 views

Truncated Negative Binomial Regression (Stata): Missing/Blank Significance value

I was running truncated negative binomial regression (tnbreg) in STATA and got the answer but when I added [pweight = weighting variable ] to weight dependent variable to address endogenous ...
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0answers
10 views

Compare related time-series count data before and after intervention

For a university library we did an intervention to create more free seating spots for students by introducing a way for students to temporarily give up their spot while away. They did this with an '...
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1answer
47 views

Rules for Percentage of zeros in a zero inflated model

What percentage of zeros in the data should make us consider trying the sequence of models: Poisson -> Negative Binomial -> Zinf-Poisson -> Zinf-Negative Binomial, etc? I have two datasets with about ...
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0answers
24 views

Use of mixed effects model for count, continuous and binary variables

I have data in the following structure: Nested: "site" (n=6) > "year" (n=6) Response: "marshland_area" (continuous) Explanatory: "sea_level" (continuous); "invasive_species" (binary); "...