Correction Notes: Correction to "An Iterative Procedure for Estimation in Contingency Tables"

Revisiting the Curtis Procedure for Boutonniere Deformity Correction

Iterative proportional scaling via decomposable submodels for contingency tables

We propose iterative proportional scaling (IPS) via decomposable submodels for maximizing likelihood function of a hierarchical model for contingency tables. In ordinary IPS the proportional scaling is performed by cycling through the members of the generating class of a hierarchical model. We propose to adjust more marginals at each step. This is accomplished by expressing the generating class...

Age correction in monitoring audiometry: method to update OSHA age-correction tables to include older workers

OBJECTIVES The US Occupational Safety and Health Administration (OSHA) Noise Standard provides the option for employers to apply age corrections to employee audiograms to consider the contribution of ageing when determining whether a standard threshold shift has occurred. Current OSHA age-correction tables are based on 40-year-old data, with small samples and an upper age limit of 60 years. By ...

An approximation algorithm for counting contingency tables

We present a randomized approximation algorithm for counting contingency tables, m × n non-negative integer matrices with given row sums R = (r1, . . . , rm) and column sums C = (c1, . . . , cn). We define smooth margins (R,C) in terms of the typical table and prove that for such margins the algorithm has quasi-polynomial NO(lnN) complexity, where N = r1 + · · · + rm = c1 + · · · + cn. Various ...

A drift correction procedure.

A procedure is introduced that can mitigate the deleterious effect of low-frequency noise [Formula: see text] often termed drift [Formula: see text] on the precision of an analytical experiment. This procedure offers several performance benefits over traditional designs based on the periodic measurement of standards to diagnose and correct for variation in instrument response. Using repeated me...