Comments on “a generalization of fisher's exact test in pxq contingency tables using more concordant relations”

The purpose of this note is to criticize Nguyen (1985) for his account of the literature on the generalization of Fisher's exact test and to point out parallels with existing algorithms of the algorithm proposed by Nguyen. Subsequently we will briefly raise some questions on the methodology proposed by Nguyen.

Nguyen (1985) suggests that all literature on exact testing prior to Nguyen & Sampson (1985) is based on the “more probable” relation or Exact Probability Test (EPT) as a test statistic. This is not correct. Yates (1934 - Pearson's X²), Lewontin & Felsenstein (1965 - X²), Agresti & Wackerly (1977 - X², Kendall's tau, Kruskal & Goodman's gamma), Klotz (1966 - Wilcoxon), Klotz & Teng (1977 - Kruskall & Wallis' H), Larntz (1978 - X², loglike-lihood-ratio statistic G², Freeman & Tukey statistic), and several others have investigated exact tests with other statistics than the EPT. In fact, Bennett & Nakamura (1963) are incorrectly cited as they investigated both X² and G², rather than EPT. Also, Freeman & Halton (1951) are incorrectly cited for they generalized Fisher's exact test to pxq tables and not 2xq tables as stated. And they are even predated by Yates (1934) who extended the test to 2×3 tables.     

Double sampling plans indexed by point of control and inflection point

Three tables for selection of double sampling plans each for the cases when n₂ = n₁and when n₂ = 2n₁with anyu one of the following combination of entry parameters are given :

1) the indifference quality level and the average out-going quality limit;

2) the indifference quality level with relative slope of the curve at that quality level and

3) the quality level corresponding to the inflection point with relative slope of the OC curve at that quality level.

Two tables enabling the transition from one set of parameters to match the OC curve of other similar sets are also given.     

ON THE USE OF X2 AS A TEST OF INDEPENDENCE IN CONTINGENCY TABLES WITH SMALL CELL EXPECTATIONS

When an r×c contingency table has many cells having very small expectations, the usual χ² approximation to the upper tail of the Pearson χ² goodness-of-fit statistic becomes very conservative. The alternatives considered in this paper are to use either a lognormal approximation, or to scale the usual χ² approximation. The study involves thousands of tables with various sample sizes, and with tables whose sizes range from 2×2 through 2×10×10. Subject to certain restrictions the new scaled χ² approximations are recommended for use with tables having an average cell expectation as small as 0·5.     

Admissible tests for exponential families with finite support 2

We state some necessary and sufficient conditions for admissibility of tests for a simple and a composite null hypotheses against ”one-sided” alternatives on multivariate exponential distributions with discrete support.

Admissibility of the maximum likelihood test for “one –sided” alternatives and z χ²test for the independence hypothesis in r× scontingency tables is deduced among others.     

Single sampling plans indexed by point op control and inflection point

Three tables for selection of single sampling plans with any one of the following combinations of entry parameters are givens.

1) the indifference quality level and the average outgoing quality limit.

2) the indifference quality level with relative slope of the OC curve at that quality leve land.

3) the quality level corresponding to the inflection point with relative slope of the OC curve at that quality level.

A table enabling the transition from one set of parameters to match the OC curve of other similar sets is also given.     

The Tale of Cochran's Rule: My Contingency Table has so Many Expected Values Smaller than 5, What Am I to Do?

In an informal way, some dilemmas in connection with hypothesis testing in contingency tables are discussed. The body of the article concerns the numerical evaluation of Cochran's Rule about the minimum expected value in r × c contingency tables with fixed margins when testing independence with Pearson's X² statistic using the χ² distribution.     

Exact Tests of Significance in Higher Dimensional Tables

We describe methods used to provide an exact test of significance of the hypothesis that all factors are mutually independent of each other in 2³ and 2⁴ contingency tables. Several numerical examples demonstrate the advantages of exact tests over approximate significance levels. We give bounds on the number of tables needed to perform this exact significance test. In four or more dimensions the number of tables in this enumeration becomes astronomical with even modest sample sizes. Inverting the characteristic function of the exact distribution has proved useful in these situations.     

On the use of diagnostic biplots in model screening for genotype by environment tables

Popular rank-2 and rank-3 models for two-way tables have geometrical properties which can be used as diagnostic keys in screening for an appropriate model. Row and column levels of two-way tables are represented by points in two or three dimensional space, whereupon collinearity and coplanarity of row and column points provide diagnostic keys for informal model choice. Coordinates are obtained from a factorization of the two-way table Y in the matrix product UV ^T. The rows of U then contain row-point coordinates and the rows of V column-point coordinates. Illustrations of applications of diagnostic biplots in the literature were restricted to data from chemistry and physics with little or no noise. In plant breeding, two-way tables containing substantial amounts of noise regularly arise in the form of genotype by environment tables. To investigate the usefulness of diagnostic biplots for model screening for genotype by environment tables, data tables were generated from a range of two-way models under the addition of various amounts of noise. Chances for correct diagnosis of the generating model depended on the type of model. Diagnostic biplots on their own do not seem to provide a sufficient means for model selection for genotype by environment tables, but in combination with other methods they certainly can provide extra insight into the structure of the data.     

A comparison of various estimators of the mean of an inverse gaussian distribution

In this paper we consider the Inverse Gaussian distribution whose variance is proportional to the mean. Assuming that the data are available from IGD(,μ,c,μ ²), and also from its length biased version, simulation studies are presented to compare the MVUE and MLE in terms of their variances and mean square errors from both kinds of data. Some tables and graphs are provided to analyze the comparisons. Finally, some recommendations and conclusions are given when one or both kinds of data are available.     

Improved likelihood ratio tests and pearson chi-square tests for independence in two dimensional contingency tables

When an I×J contingency table has many cells having very small frequencies, the usual chi-square approximation to the upper tail of the likelihood ratio goodness-of-fit statistic, G² and Pearson chi-square statistic, X², for testing independence, are not satisfactory. In this paper we consider the problem of adjusting G² and X². Suitable adjustments are suggested on the basis of analytical investigation of asymptotic bias terms for G² and X². A Monte Carlo simulation is performed for several tables to assess the adjustments of G² and X² in order to obtain a closer approximation to the nominal level of significance.     

Catanova for multidimensional contingency tables: Nominal-scale response

This paper extends an analysis of variance for categorical data (CATANOVA) procedure to multidimensional contingency tables involving several factors and a response variable measured on a nominal scale. Using an appropriate measure of total variation for multinomial data, partial and multiple association measures are developed as R² quantities which parallel the analogous statistics in multiple linear regression for quantitative data. In addition, test statistics are derived in terms of these R² criteria. Finally, this CATANOVA approach is illustrated within the context of 2 three-way contingency table from a multicenter clinicaltrial.     

Modified tables for the selection of qss–1 quick switching system for a given (aql,lql)

This paper presents a set of new tables and procedures for the selection of the following three types of Quick Switching (QS) systems for a given Acceptable Quality Level (AQL), Limiting Quality Level (LQL), producer's risk and consumer's risk.

(1) A Single sampling QS system with equal sample sizes but with different acceptance numbers

(2) A Single sampling QS system with two different sample sizes but with same acceptance number and

(3) A QS systen with double sampling normal inspection and single sampling tightened inspection

The third type of QS systen is the one newly presented in this paper. The tables provide unique plans for a given set of conditions as well as providing a smaller sample size or a smaller sum of Average Sample Numbers(ASN) at the AQL and LQL     

On the decomposition of X2 for two-way contingency tables

When samples are taken independently from I populations and the subjects classified into J categories, can the Pearson's chisquare statistic X² testing the homogeneity model on the resulting I×J two-way table be decomposed into components familiar in the analysis of variance? Will the X² testing the homogeneity model on tables derived by collapsing columns in the spirit of orthogonal comparisons in factorial experiments be asymptotically independent? The answers to both questions are generally negative. This paper gives a theoretical justification.     

Bayesian Analysis of Contingency Tables

ABSTRACT

The display of the data by means of contingency tables is used in different approaches to statistical inference, for example, to broach the test of homogeneity of independent multinomial distributions. We develop a Bayesian procedure to test simple null hypotheses versus bilateral alternatives in contingency tables. Given independent samples of two binomial distributions and taking a mixed prior distribution, we calculate the posterior probability that the proportion of successes in the first population is the same as in the second. This posterior probability is compared with the p-value of the classical method, obtaining a reconciliation between both results, classical and Bayesian. The obtained results are generalized for r × s tables.     

Complete moment convergence of weighted sums for arrays of negatively dependent random variables and its applications

For testing goodness-of-fit in a k cell multinomial distribution having very small frequencies, the usual chi-square approximation to the upper tail of the likelihood ratio statistic, G² is not satisfactory. A new adjustment to G² is determined on the basis of analytical investigation in terms of asymptotic bias and variance of the adjusted G² A Monte Carlo simulation is performed for several one-way tables to assess the adjustment of G² in order to obtain a closer approximation to the nomial level of significance.     

Markov chain Monte Carlo tests for designed experiments

We consider conditional exact tests of factor effects in designed experiments for discrete response variables. Similarly to the analysis of contingency tables, a Markov chain Monte Carlo method can be used for performing exact tests, when large-sample approximations are poor and the enumeration of the conditional sample space is infeasible. For designed experiments with a single observation for each run, we formulate log-linear or logistic models and consider a connected Markov chain over an appropriate sample space. In particular, we investigate fractional factorial designs with 2^p-q$2^{p-q}$ runs, noting correspondences to the models for 2^p-q$2^{p-q}$ contingency tables.     

Formulas for the Design of CUSUM Quality Control Charts

ABSTRACT

In the design of CUSUM control charts, it is common to use charts, tables, or software to find an appropriate critical threshold (h). This article provides an approximate formula to calculate the threshold directly from prespecified values of the reference value (k) and the in-control average run length (ARL₀). Formulas are also provided for choosing k and h from prespecified values of the in-control and out-of-control average run lengths.     

On the adequacy of the chi-squared approximation for the coefficient of variation

The X² approximation to the distribution of the sample coefficient of variation of a normally distributed random variable, due to McKay 1932 is not nearly as accurate as suggested by the confirmatory studies of Fieller 1932 and Pearson 1932.The approximation will, however, be adequate in many practical situations and has the convenience of requiring nothing more than the readily available tables of x².     

TEST OF FIT FOR THE INVERSE GAUSSIAN AND GAMMA DISTRIBUTIONS UNDER CENSORING

The problem of testing the fit of the inverse Gaussian and the gamma distribution when the sample is censored and some of the parameters are unknown, is studied. Empirical Distribution Function (EDF) statistics, namely Cramér-von Mises' W ² and the Anderson-Darling's A ², are used. The limiting covariance functions of the corresponding empirical processes are derived. Asymptotic percentage points are given for some parameter values and censoring proportions. Moreover, a numerical routine is made available upon request, to obtain p-values for both test statistics, thus eliminating the need of tables and interpolation. Finally, a simple Monte Carlo study is presented to evaluate first, the approximation when using the asymptotic distributions in finite samples and second, to support the use of estimated parameter values instead of the unknown parameters needed in the limiting covariance function.     

Hierarchical clustering and matrix completion for the reconstruction of world input–output tables

Multi-regional input–output (I/O) matrices provide the networks of within- and cross-country economic relations. In the context of I/O analysis, the methodology adopted by national statistical offices in data collection raises the issue of obtaining reliable data in a timely fashion and it makes the reconstruction of (parts of) the I/O matrices of particular interest. In this work, we propose a method combining hierarchical clustering and matrix completion with a LASSO-like nuclear norm penalty, to predict missing entries of a partially unknown I/O matrix. Through analyses based on both real-world and synthetic I/O matrices, we study the effectiveness of the proposed method to predict missing values from both previous years data and current data related to countries similar to the one for which current data are obscured. To show the usefulness of our method, an application based on World Input–Output Database (WIOD) tables—which are an example of industry-by-industry I/O tables—is provided. Strong similarities in structure between WIOD and other I/O tables are also found, which make the proposed approach easily generalizable to them.