Asymptotic Relative Efficiency of Some Jackknife Estimators of a Common Odds Ratio

In the situation of several 2 × 2 tables the asymptotic relative efficiencies of certain jackknife estimators of a common odds ratio are investigated in the case that the number of tables is fixed while the sample sizes within each table tend to infinity. The estimators show very good results over a wide range of parameters. Some situations in which the estimators have low asymptotic relative efficiency are pointed out:.     

The Power Function of the Test for ‘No Three Factor Interaction’ in 2×2×2 Contingency Tables

Three approximations to the power function of the chi-square test for the hypotheses of ‘no three factor interaction’ in a 2 × 2 × 2 contingency table are introduced and compared. The first method is based on the sampling distribution of the logarithm of the odds ratio, the second-on the non-central X² distribution and the third—on the conditional distribution of a cell entry. The last method is found to provide the closest approximation under various alternative hypotheses and sample sizes.     

A Modified MANN-WHITNEY Test with Improved Asymptotic Relative Efficiency

A slight modification of the MANN -WHITNEY test is introduced here. When the underlying distribution is normal the ARE of the modified test with respect to t-test is 99.22% (MANN -WHITNEY test: 95.45%). The lower bound of the ARE of the modified test is 92.50% for all distributions with a continuous density function and a finite variance (MANN -WHITNEY test: 86.4%).     

A Modified Exact Test for 2 × 2 Contingency Tables

A modified exact test is proposed for 2×2 contingency tables. This test, which is based on a less conservative definition of the concept of significance (STONE, 1969) is compared with a modified form of Pearson's X² test and with Tocher's randomized exact (UMPU) test. The sizes of the new test lie near the nominal 0.05 levels while those of the X² test usually exceed the nominal level, sometimes by a factor of 2 or more. The power of the modified test is usually close to that of the UMPU test.     

Test for increasing convex order in multivariate response

Trend test based on cross-classified data in dose-response has been a central problem in medicine. Most of existing test methods are known to only fit to binary response variables. However, the approaches for binary response tables may suffer from the lack of a clear choice for dichotomization. For multivariate response with ordered categories, some studies have been done for simple stochastic order, likelihood ratio order and so on. However, methods of statistical inference on increasing convex order for more than two multinomial populations have not been fully developed. For testing the increasing convex order alternative, this article provides a model-free test method which can be used in the case of two-way tables and stratified data. Two real examples will be used to illustrate how to apply our test method.     

Variances and Asymptotic Distributions of Direct Standardized Rates

Formulas for the variance of direct standardized rates are given for three different sampling models. The three models are product multinomial models when population totals are fixed by design, or strata totals are fixed by design, or cell (each population—each stratum) totals are fixed by design. Asymptotic distributions are derived for each model. A discussion on the relevance and use of standardized rates and the need for distribution theory is also provided.     

Size and Power of Test Statistics for Gene Correlation in 2 × 2 Contingency Tables

Monte Carlo simulation of size and power of two proposed tests for linkage disequilibrium between two genes each with two alleles were investigated. Results were compared with two commonly used statistics, the correlation coefficient r and the log-odds ratio tests. Depending on the sign of the linkage disequilibrium, the new tests were found to be more powerful than either of the correlation or log-odds ratio tests. However, on average (positive and negative linkage disequilibrium) the Chi-square test using the correlation coefficient was to a small extent more powerful than the other tests.     

Unconditional versions of several tests commonly used in the analysis of contingency tables

By focusing on a confidence interval for a nuisance parameter, Berger and Boos (1994, Journal of the American Statistical Association 89, 1012-1016) proposed new unconditional tests. In particular, they showed that, for a 2 x 2 table, this procedure generally was more powerful than Fisher's exact test. This paper utilizes and extends their approach to obtain unconditional tests for combining several 2 x 2 tables and testing for trend and homogeneity in a 2 x K table. The unconditional procedures are compared to the conditional ones by reanalyzing some published biomedical data.     

Small Sample Properties of the Mantel-Haenszel Test Statistic for Density Follow-Up Studies

For the analysis of combinations of 2×2 non-contingency tables as obtained from density follow-up studies (relating a number of events to a number of person-years of follow-up) an analogue of the Mantel-Haenszel test for 2×2 contingency tables is widely used. In this paper the small sample properties of this test, both with and without continuity correction, are evaluated. Also the improvement of the test-statistic by using the first four cumulants via the Edgeworth expansion was studied. Results on continuity correction agree with similar studies on the Mantel-Haenszel statistic for 2×2 contingency tables: Continuity correction gives a p-value which approximates the exact p-value better than the p-value obtained without this correction; both the exact test and its approximations show considerable conservatism in small samples; the uncorrected Mantel-Haenszel test statistic gives a p-value that agrees more with the nominal significance level, but can be anti-conservative. The p-value based on the first four cumulants gives a better approximation of the exact p-value than the continuity corrected test, especially when the distribution has marked skewness.     

Test Procedures in Configural Frequency Analysis (CFA) Controlling the Local and Multiple Level

The test statistics used until now in the CFA have been developed under the assumption of the overall hypothesis of total independence. Therefore, the multiple test procedures based on these statistics are really only different tests of the overall hypothesis. If one likes to test a special cell hypothesis, one should only assume that this hypothesis is true and not the whole overall hypothesis. Such cell tests can then be used as elements of a multiple test procedure. In this paper it is shown that the usual test procedures can be very anticonservative (except of the two-dimensional, and, for some procedures, the three-dimensional case), and corrected test procedures are developed. Furthermore, for the construction of multiple tests controlling the multiple level, modifications of Holm's (1979) procedure are proposed which lead to sharper results than his general procedure and can also be performed very easily.     

The Relative Power of Two Asymptotic Multivariate Tests for Homogeneity in a Contingency Table

In a three way contingency table two multivariate tests for homogeneity have been proposed by the author (1983) a the “catanova” test, which is a trace “metric” test and b the “multinova” test which is determinant based. Both tests are asymptotically distributed as chi-square. In this paper, the power values of the tests are compared and conditions are given for preference of each test.     

Asymptotic Efficiency of the Chi-Square Test for Heterogeneity of Proportions in Some Sparse-Data Cases

We consider the problem of testing for heterogeneity of K proportions when K is not small and the binomial sample sizes may not be large. We assume that the binomial proportions are normally distributed with variance σ². The asymptotic relative efficiency (ARE) of the usual chi-square test is found relative to the likelihood-based tests for σ²=0. The chi-square test is found to have ARE = 1 when the binomial sample sizes are all equal and high relative efficiency for other cases. The efficiency is low only in cases where there is insufficient data to use the chi-square test.     

The Power of the Mantel-Haenszel Test when Adjustment is by the True or Estimated Propensity Score

The power of the Mantel-Haenszel test for no treatment effect in the case of binary exposure and response variates was examined through simulation studies when subclasses were formed on the basis of the true and estimated propensity scores and by direct stratification on two continuous covariates. The power of these tests was also compared to the score test in a misspecified logistic regression model. In general adjustment by the true propensity score was most likely to reject a false null hypothesis, the score test was more likely to reject a false null hypothesis than the Mantel-Haenszel test when adjustment is by the estimated propensity score or subclassification on the covariates. There was litte difference in the observed powers of the Mantel-Haenszel tests between adjustment by the estimated propensity score and subclassification on the covariates.     

Sequentially Rejective Test Procedures for Detecting Outlying Cells in One- and Two-Sample Multinomial Experiments

For multiple testing of multinomial models in the case of one or two samples we propose using test procedures based on the principle described by MARCUS, PERITZ and GABRIEL (1976). These methods are based in each step of the sequentially rejective strategy on tests which exhaust the full α level (i.e. which are not conservative). The tests can be performed in a finite or asymptotic version.