Journal article
Performing T-tests to Compare Autocorrelated Time Series Data Collected from Direct-Reading Instruments
Journal of Occupational and Environmental Hygiene, Vol.12(11), pp.743-752
11/02/2015
DOI: 10.1080/15459624.2015.1044603
PMID: 26011524
Abstract
Industrial hygienists now commonly use direct-reading instruments to evaluate hazards in the workplace. The stored values over time from these instruments constitute a time series of measurements that are often autocorrelated. Given the need to statistically compare two occupational scenarios using values from a direct-reading instrument, a t-test must consider measurement autocorrelation or the resulting test will have a largely inflated type-1 error probability (false rejection of the null hypothesis). A method is described for both the one-sample and two-sample cases which properly adjusts for autocorrelation. This method involves the computation of an "equivalent sample size" that effectively decreases the actual sample size when determining the standard error of the mean for the time series. An example is provided for the one-sample case, and an example is given where a two-sample t-test is conducted for two autocorrelated time series comprised of lognormally distributed measurements.
Details
- Title: Subtitle
- Performing T-tests to Compare Autocorrelated Time Series Data Collected from Direct-Reading Instruments
- Creators
- Patrick O'Shaughnessy - Department of Occupational and Environmental Health, College of Public Health, The University of IowaJoseph E Cavanaugh - Department of Biostatistics, College of Public Health, The University of Iowa
- Resource Type
- Journal article
- Publication Details
- Journal of Occupational and Environmental Hygiene, Vol.12(11), pp.743-752
- DOI
- 10.1080/15459624.2015.1044603
- PMID
- 26011524
- NLM abbreviation
- J Occup Environ Hyg
- ISSN
- 1545-9624
- eISSN
- 1545-9632
- Publisher
- Taylor & Francis
- Language
- English
- Date published
- 11/02/2015
- Academic Unit
- Statistics and Actuarial Science; Civil and Environmental Engineering; Occupational and Environmental Health; Biostatistics; Injury Prevention Research Center
- Record Identifier
- 9983985840502771
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