เปรียบเทียบวิธี

	คะแนน M-Score ของ Beneish: การตรวจจับการบิดเบือนกำไร	การถดถอยโลจิสติก
สาขาวิชา	การเงิน	สถิติการวิจัย
ตระกูล	Regression model	Process / pipeline
ปีกำเนิด	1999	1958
ผู้ริเริ่ม	Messod Beneish	David Roxbee Cox
ประเภท	Probabilistic forensic accounting model	Method
แหล่งต้นตำรับ	Beneish, M. D. (1999). The detection of earnings manipulation. Financial Analysts Journal, 55(5), 24–36.	Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242.
ชื่อเรียกอื่น	Beneish Model, M-Score Model, Earnings Manipulation Score, Beneish M-Skoru	logit model, binomial logistic regression, LR
ที่เกี่ยวข้อง	3	3
สรุป	The Beneish M-Score is a statistical model developed by Messod Beneish in 1999 to identify whether a company has manipulated its reported earnings. The model combines eight financial-statement ratios into a single composite score using coefficients estimated from a probit regression on a sample of detected earnings manipulators. A score above −2.22 indicates a heightened probability of manipulation, making the M-Score a widely used tool in forensic accounting and investment due-diligence.	Logistic regression is a statistical method for modeling the probability of a binary outcome (disease present/absent, success/failure) as a function of continuous and categorical predictors. Developed by David Roxbee Cox (1958), it solves the problem of predicting categorical outcomes by applying a logistic transformation to constrain predictions to the [0,1] probability interval, enabling accurate risk stratification, diagnostic prediction, and causal inference in epidemiology, medicine, and social science.