Profile likelihood for estimation and confidence intervals

Normal-based confidence intervals for a parameter of interest are inaccurate when the sampling distribution of the estimate is nonnormal. The technique known as profile likelihood can produce confidence intervals with better coverage. It may be used when the model includes only the variable of interest or several other variables in addition. Profile-likelihood confidence intervals are particularly useful in nonlinear models. The command pllf computes and plots the maximum likelihood estimate and profile likelihood–based confidence interval for one parameter in a wide variety of regression models.


Issue Date:
2007
Publication Type:
Journal Article
DOI and Other Identifiers:
st0132 (Other)
PURL Identifier:
http://purl.umn.edu/119282
Published in:
Stata Journal, Volume 07, Number 3
Page range:
376-387
Total Pages:
12

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 Record created 2017-04-01, last modified 2017-08-26

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