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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16 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
22 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 ...
0
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1answer
28 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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0answers
22 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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0answers
12 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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15 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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0answers
21 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 ...
0
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0answers
14 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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0answers
24 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 ...
3
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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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0answers
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
94 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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38 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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0answers
36 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 ...
0
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0answers
24 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
635 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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0answers
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 ...
0
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0answers
12 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
38 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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0answers
17 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 ...
4
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1answer
73 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 ...
0
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1answer
39 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
33 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. ...
0
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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 ...
0
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0answers
9 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
16 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
32 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 ...
0
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0answers
33 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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0answers
19 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 ...
0
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1answer
29 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 ...
3
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1answer
17 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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0answers
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 ...
2
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1answer
57 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 ...
0
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0answers
15 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 ...
0
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0answers
15 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
9 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 ...
0
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1answer
41 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 ...
0
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0answers
22 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); ...
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1answer
42 views

Test if number of fish differ by location

I have a dataset which consists of location ID's (1 to 29 different locations) and each location has a couple of repeated measures (max n = 780, min n = 50). Each measurement consists of a number of ...
0
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1answer
20 views

Confidence level of a sample of count data

I have a sample of count data (N = 226) representing a parameter of a population. The sample contains many zero values and a few non-zero values. How can I best estimate the level of confidence that ...
3
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2answers
67 views

After how many events can you say the failure rate of one piece of equipment is greater than another?

If there exist two identical pieces of equipment, in this case two pumps that are the exact same (in theory) pumping the same fluid in the same location at the same rate (everything is the same), how ...
3
votes
1answer
74 views

Time-dependent Poisson regression

I have a time series that count the number of "type 1" events in a city, for each day. The serie contains a lot of zeros because type 1 events are rare (about 80% of counts are zeros). I'm using a ...
0
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0answers
42 views

How to calculate standard error for WEIGHTED count data aka proportions

First let me explain my data. I have 30 residential subdivisions. Within each subdivision, I randomly generated n=50 points over an aerial photograph. For each subdivision, I counted how many points ...
3
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1answer
64 views

Confidence interval for population mean when sample is a series of counts?

I have count data for each of a sample of individuals (it's the number of times each independent individual performed a certain behaviour during a standardised observation of that individual). How can ...
0
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2answers
24 views

General linear model for counts which are “correlated”

The typical general linear model (GLM) for count data uses the Poisson link function. The counts there are assumed to be "independent". Now suppose the counts are not "independent" in a sense ...
5
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2answers
122 views

Can I ignore under-dispersion in my count data?

I have under-dispersed count data. I do not want to transform them, and using a negative binomial error distribution (via glmer.nb) does not help. My results are the same regardless of the ...
11
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1answer
639 views

Diagnostics for generalized linear (mixed) models (specifically residuals)

I am currently struggling with finding the right model for difficult count data (dependent variable). I have tried various different models (mixed effects models are necessary for my kind of data) ...
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1answer
44 views

Multicollinearity in Zero Inflated Negative Binomial Regression

I am trying to model counts govt, based on the counts lp,const,...
0
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1answer
24 views

modeling count data with underdispersion

I modeled the count data with poisson regression and the pearson chi square divided by the degrees of freedom was 0.25 suggesting under-dispersion , what can I do , is it possible to deal with this ...