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Similarly, an 8% to a 32% increase was observed when Poisson extension of log binomial regression was carried out to estimate the cumulative effect of repeated lesion-visits on the probability of detectable plasma HIV RNA at the last or 3rd study visit (Table 5, trend p-value = 0.004).
Zero-truncated negative binomial regression was carried out to predict length of stay.
For analysis of plaque score, negative binomial regression was carried out with additional adjustment for the number of missing scans.
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In order to test the proposed model, a binomial logistic regression was carried out.
Log binomial regression was used to calculate adjusted PRs.
A negative binomial regression was used due to over dispersion.
Negative binomial regression was used instead of Poisson regression to account for overdispersion in the data.
Negative binomial regression was used instead of Poisson regression because of the over-dispersed data.
Negative binomial regression would be chosen if the p-value of the Vuong test was not significant (p > 0.05) indicating the zero-inflated negative binomial regression was not significantly better than the negative binomial regression.
Negative binomial regression was chosen because some count data were overdispersed (Kim and Kriebel, 2009).
Negative binomial regression was used to analyse the differences in GP visits between the two years.
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