(Q23915659)

English

Inferences on the means of lognormal distributions using generalized p-values and generalized confidence intervals

journal article published in 2003

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19 July 2017

Inferences on the means of lognormal distributions using generalized p-values and generalized confidence intervals (English)

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12 July 2017

National Institute for Occupational Safety and Health

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2 references

29 March 2020

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29 March 2020

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K Krishnamoorthy

1

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Thomas Mathew

series ordinal

2

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language of work or name

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July 2003

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published in

Journal of Statistical Planning and Inference

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volume

115

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issue

1

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page(s)

103-121

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performing organization

University of Maryland, Baltimore

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University of Maryland, Baltimore

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NIOSHTIC-2

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2 February 2024

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Wikimedia–NIOSH collaboration

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maintained by WikiProject

WikiProject Mathematics

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25 September 2023

The logarithm in biology. 1. Mechanisms generating the log-normal distribution exactly

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https://api.crossref.org/works/10.1016%2FS0378-3758%2802%2900153-2

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7 January 2021

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Assessing occupational exposure via the one-way random effects model with balanced data

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https://api.crossref.org/works/10.1016%2FS0378-3758%2802%2900153-2

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7 January 2021

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On strategies for comparing occupational exposure data to limits

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https://api.crossref.org/works/10.1016%2FS0378-3758%2802%2900153-2

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7 January 2021

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A method for evaluating the mean exposure from a lognormal distribution

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7 January 2021

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Exact inference for growth curves with intraclass correlation structure

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https://api.crossref.org/works/10.1016%2FS0378-3758%2802%2900153-2

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7 January 2021

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Confidence intervals for the log-normal mean .

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stated in

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https://api.crossref.org/works/10.1016%2FS0378-3758%2802%2900153-2

retrieved

7 January 2021

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Methods for comparing the means of two independent log-normal samples

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stated in

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7 January 2021

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Identifiers

DOI

10.1016/S0378-3758(02)00153-2

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NIOSHTIC-2 ID

20026061

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ResearchGate publication ID

222535047

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zbMATH Open document ID

1041.62023

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(Q23915659)

Inferences on the means of lognormal distributions using generalized p-values and generalized confidence intervals

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