Inferring About the Average Value of Audit Errors from Sequential Ratio Tests

The book amounts are modeled as values of a random variable, represented by a mixture of distributions of both the correct and error-contaminated amounts. The mixing coefficient represents the proportion of items with non-zero error amounts. This study addresses the problem of determining the sample size needed for testing statistical hypotheses regarding mean accounting errors. The average sample size is estimated using the Sequential Probability Ratio Test (SPRT), applying the Monte Carlo method. Estimating average audit errors is a common challenge in economic research.

Authors

Institutions

Publication Details

Journal
Entropy
Published
2024-11-20
DOI
https://doi.org/10.3390/e26110998
Citations
2
Primary Topic
Forecasting Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.98
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Inferring About the Average Value of Audit Errors from Sequential Ratio Tests

Mariusz Pleszczyński, Grzegorz Sitek
2 citations
Entropy
Forecasting Techniques and Applications
0.98
article

Inferring About the Average Value of Audit Errors from Sequential Ratio Tests

Mariusz Pleszczyński, Grzegorz Sitek
article en
2 citations

Abstract

The book amounts are modeled as values of a random variable, represented by a mixture of distributions of both the correct and error-contaminated amounts. The mixing coefficient represents the proportion of items with non-zero error amounts. This study addresses the problem of determining the sample size needed for testing statistical hypotheses regarding mean accounting errors. The average sample size is estimated using the Sequential Probability Ratio Test (SPRT), applying the Monte Carlo method. Estimating average audit errors is a common challenge in economic research.

EntropyVol. 26(11)
Silesian University of Technology (PL), University of Economics in Katowice (PL)
Decent work and economic growth
Openalex Percentile: Top 20%
Forecasting Techniques and Applications
0.98
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.