negative binomial

Hi Everyone, I have a question about the best model to use for this analysis. The question I am trying to analyze is - What is the association between Indicator 1 and age, sex, and group? Data is measured on a facility/site. This is a random effect. The data are aggregated within the site by...

Hi. Are these question the same(except the parameters of course) : First - What's the number of trials needed until having at least 1 defective product, with a probability >= 85%, with pDef = 0.03. Second - What's the number of trails needed until having at least 5 defective product, with a...

Hello guys, I wish to model the number of days patients stayed in a clinic. Some of my predictors included: type of injury/disease, age, insurance, etc. Since days are count data and my data is over-dispersed, negative binomial models seem to be the appropriate technique. However, I know that...

Hey guys! Apologies for the potentially *stupid* question... I'm *very* rusty on my maths and am not getting anywhere with Google's support. I'm a marketeer, looking at how/if it may be possible to estimate a NBD curve from a limited dataset... my client has given me some 'data' about...

Hi, I have a dataset spanning two years which consists of individuals entering some process. Once they have entered this process I want to predict the number of days they will remain in this process based on some set of covariates. There are some charateristics of the data which lead me to...

Hello, I'm a bit confused between the difference between scaling and centring in a negative binomial regression. My model looks like this: invertebrate abundance= Year +shoot count + epiphyte biomass(g) + epiphyte bio*shoot count Years: 2015, 2016 Shoot count range:1-30 Epiphyte bio...

Hello friends, I've used a negative binomial GLM to look at how invertebrate abundance (over dispersed) is affected by seagrass density. There is a negative interaction between seagrass density and epiphyte biomass (the little plants growing on seagrass blades that invertebrates eat)...

Hello everyone, I am a newby to that forum, so I hope my question is not redundant. I am currently sitting on my master thesis where I investigate which effect diversity in teams has on publications. Herefore, I have a dependent variable 'publications' which is a count variable. I have two...

Hello dear forum members, For a time being I had been working with the following model (Stata command format): - xtpoisson y x1 x2 x3 x4 x5, fe- where, y(it) is a count DV, x1-x2(it) are controls, and x3-x5(it) are the predictors of interest, i -- denotes an individual (N = 1750), and t...

Hello everyone, I've used a negative binomial model to predict invertebrate densities. The model fits but is not significant, so I don't want to waste space with a graph in my final report. I want to make simple table showing the coefficients and p values. Does anyone have an example...

Hello dear forum members, My study aims to address the question about physician ratings: Do they have an impact on the business value (as proxied with new patient referrals)? The sample is a panel of of U.S. oncologists (N=1,694) observed from 2009 to 2013. The outcome is a count, so for the...

Dear All, I have attribute that show overdispersion and seem to be distributed according to a negative binomial distribution. I have the following questions: 1. How can I check in Minitab if my data is distributed according to Negative Binomial? (I used Crystal Ball for this specific...

Hello, My outcome is Sugar intake with a highly skewed continuous outcome variable. The histogram and variable details are Attached. Since the distribution is highly skewed and has a very high variance (12.78) compared to the mean (2.67) I thought I could round each decimal to the nearest...

When using a GLM or GLMM with a negative binomial distribution in R it is usually necessary to set the value of theta in the model. But what does theta actually stand for? And how do I caluclate it? I have been able to get around this for now by setting my models to calculate theta for me...

Hi all, I am fairly new to the R world. I need some help with correct syntax for running a negative binomial regression/zero-inflation negative binomial regression on some data. I am trying to run a regression that looks at how race/ethnicity influences the number of summer meal sites in a...

Hi, I am doing an assignment on unemployment (DV) and racial discrimination - specifically african-american population - and I am in doubt whether to use percent of resident population black resident alone, or black alone resident population. If I use the latter, would I need to switch from an...

Assume City A has three parties, Party B, Party C, and Party D, with n1, n2, n2 citizens in them, respectively. Assume, for people in B, they will always support the motion by the government, while, for people in C, they will always be against the government. However, those in D will support the...

I have been using a negative binomial distribution to describe my data; in order to allow me to randomly sample from the parameterised distributions. I have had no problems getting r (the number of successes) and p (the probability of success) for my distribution. My problem is that I would like...

Hi there, I have a negative binomial model of count data with an offset (total counting effort) in R: L1<-glm.nb(counts~offset(log(total.counts))+temperature, link='log', data=dat) and I want to compare it to the null model. Am I right in thinking I can just do...

Thank you so much anyone... I have the results of a negative binomial where the DV is the log count of meals obtained. I have continuous predictors and I have my DV back logged, i.e., exp(b) with CIs for easier interpretation in my paper. The thing is... I am not easily interpreting my exp(b)...