RT Journal Article SR Electronic T1 Environmental Monitoring: Setting Alert and Action Limits Based on a Zero-Inflated Model JF PDA Journal of Pharmaceutical Science and Technology JO PDA J Pharm Sci Technol FD Parenteral Drug Association (PDA) SP 2 OP 8 DO 10.5731/pdajpst.2013.00897 VO 67 IS 1 A1 Harry Yang A1 Wei Zhao A1 Terrence O'day A1 William Fleming YR 2013 UL http://journal.pda.org/content/67/1/2.abstract AB The primary purpose of an environmental monitoring program is to provide oversight for microbiological cleanliness of manufacturing operation and document the state of control of the facility. Key to the success of the program is the establishment of alert and action limits. In practice, several statistical methods including normal, Poisson, and negative binomial modeling have been routinely used to set these limits. However, data collected from clean rooms or controlled locations often display excess of zeros and overdispersion, caused by sampling population heterogeneity. Such data render it inappropriate to use the traditional methods to set alert and action levels. In this paper, a method based on a zero-inflated negative binomial model is proposed for the above instances. The method provides an enhanced alternative for trending environmental data of classified rooms, and it is demonstrated to show a clear improvement in terms of model fitting and parameter estimation. LAY ABSTRACT: The primary purpose of an environmental monitoring program is to provide oversight for microbiological cleanliness of manufacturing operation and document the state of control of the facility. Key to the success of the program is the establishment of alert and action limits. In practice, several statistical methods including normal, Poisson, and negative binomial modeling have been routinely used to set these limits. However, data collected from clean rooms or controlled locations often display excess of zeros and overdispersion, caused by sampling population heterogeneity. Such data render it inappropriate to use the traditional methods to set alert and action levels. In this paper, a method based on a zero-inflated negative binomial model is proposed for the above instances. The method provides an enhanced alternative for trending environmental data of classified rooms, and it is demonstrated to show a clear improvement in terms of model fitting and parameter estimation.