Exact tests in binary data under an incomplete block crossover design

2016 ◽  
Vol 27 (2) ◽  
pp. 579-592 ◽  
Author(s):  
Kung-Jong Lui ◽  
Kuang-Chao Chang
Keyword(s):  
Binary Data ◽  
Logistic Regression Model ◽  
Crossover Trial ◽  
Test Procedure ◽  
Crossover Design ◽  
Incomplete Block ◽  
Primary Dysmenorrhea ◽  
Test Procedures ◽  
Exact Test ◽  
High Doses

To improve the power of a parallel groups design and reduce the time length of a crossover trial, we may consider an incomplete block crossover design. Under a distribution-free random effects logistic regression model, we derive an exact test and a Mantel-Haenszel Type of summary test procedure for testing non-equality in binary data when comparing three treatments. We employ Monte Carlo simulation to evaluate the performance of these test procedures. We find that both test procedures developed here can perform well in a variety of situations. We use the data taken as a part of the crossover trial comparing the low and high doses of an analgesic with a placebo for the relief of pain in primary dysmenorrhea to illustrate the use of the proposed test procedures.

scholarly journals Testing Equality of Treatments under an Incomplete Block Crossover Design with Ordinal Responses

2017 ◽  
Vol 13 (1) ◽  
Author(s):  
Kung-Jong Lui
Keyword(s):  
Ordinal Data ◽  
Crossover Trial ◽  
Crossover Design ◽  
Incomplete Block ◽  
Finite Sample ◽  
Test Procedures ◽  
Advantages And Disadvantages ◽  
Relative Treatment Effect ◽  
Patient Responses ◽  
High Doses

AbstractThe generalized odds ratio (GOR) for paired sample is considered to measure the relative treatment effect on patient responses in ordinal data. Under a three-treatment two-period incomplete block crossover design, both asymptotic and exact procedures are developed for testing equality between treatments with ordinal responses. Monte Carlo simulation is employed to evaluate and compare the finite-sample performance of these test procedures. A discussion on advantages and disadvantages of the proposed test procedures based on the GOR versus those based on Wald’s tests under the normal random effects proportional odds model is provided. The data taken as a part of a crossover trial studying the effects of low and high doses of an analgesic versus a placebo for the relief of pain in primary dysmenorrhea over the first two periods are applied to illustrate the use of these test procedures.

Testing equality and interval estimation of the generalized odds ratio in ordinal data under a three-period crossover design

2015 ◽  
Vol 26 (3) ◽  
pp. 1165-1181 ◽  
Author(s):  
Kung-Jong Lui ◽  
Kuang-Chao Chang ◽  
Chii-Dean Lin
Keyword(s):  
Odds Ratio ◽  
Ordinal Data ◽  
Interval Estimation ◽  
Crossover Design ◽  
Test Procedures ◽  
Exact Test ◽  
Number Of Patients ◽  
Interval Estimators ◽  
High Doses ◽  
Stratified Analysis

The crossover design can be of use to save the number of patients or improve power of a parallel groups design in studying treatments to noncurable chronic diseases. We propose using the generalized odds ratio for paired sample data to measure the relative effects in ordinal data between treatments and between periods. We show that one can apply the commonly used asymptotic and exact test procedures for stratified analysis in epidemiology to test non-equality of treatments in ordinal data, as well as obtain asymptotic and exact interval estimators for the generalized odds ratio under a three-period crossover design. We further show that one can apply procedures for testing the homogeneity of the odds ratio under stratified sampling to examine whether there are treatment-by-period interactions. We use the data taken from a three-period crossover trial studying the effects of low and high doses of an analgesic versus a placebo for the relief of pain in primary dysmenorrhea to illustrate the use of these test procedures and estimators proposed here.

Notes on Test and Estimation in Comparison of Three Treatments under A Simple Carry-Over Three-Period Model

2018 ◽  
Vol 14 (1) ◽  
Author(s):  
Kung-Jong Lui
Keyword(s):  
Type I Error ◽  
Average Length ◽  
Test Procedure ◽  
Forced Expiratory Volume ◽  
Crossover Design ◽  
Type I ◽  
Test Procedures ◽  
Double Blind ◽  
Interval Estimators ◽  
Carry Over

Abstract Under the three-treatment three-period crossover design with simple carry-over effects, we derive the least-squares estimators for period effects, treatment effects and carry-over effects, as well as their covariance matrix in closed and explicit expressions. Using Monte Carlo simulation, we compare the test procedure adjusting carry-over with that ignoring carry-over with respect to Type I error and power. We further compare interval estimators adjusting carry-over with those ignoring carry-over with respect to the coverage probability and the average length. When the variation of responses within patients is small, the test procedure and interval estimators ignoring carry-over can lose accuracy in the presence of carry-over effects. When the variation of responses within patients is large, this loss of accuracy may become small or even minimal. We note that the loss of efficiency due to the adjustment of carry-over under the simple carry-over three-period crossover design is moderate, and is much less than that found for a two-period crossover design. We use the double-blind three-period crossover trial comparing formoterol solution aerosol and salbutamol suspension aerosol with a placebo for patients suffering from exercise-induced asthma on the forced expiratory volume in one second (FEV1) to illustrate the use of test procedures and interval estimators discussed here.

Reliability of Laboratory Tests for the Control of Oral Anticoagulation

1974 ◽  
Vol 32 (02/03) ◽  
pp. 483-491
Author(s):  
E. A Loeliger ◽  
M. J Boekhout-Mussert ◽  
L. P van Halem-Visser ◽  
J. D. E Habbema ◽  
H de Jonge
Keyword(s):  
Human Brain ◽  
Laboratory Tests ◽  
Test Procedure ◽  
Rabbit Brain ◽  
Normal Range ◽  
Test Procedures ◽  
Discrimination Power ◽  
Power Of The Test ◽  
Assay Procedure ◽  
Low Sensitivity

SummaryThe present study concerned the reproducibility of the so-called prothrombin time as assessed with a series of more commonly used modifications of the Quick’s onestage assay procedure, i.e. the British comparative reagent, homemade human brain thromboplastin, Simplastin, Simplastin A, and Thrombotest. All five procedures were tested manually on pooled lyophilized normal and patients’ plasmas. In addition, Simplastin A and Thrombotest were investigated semiautomatically on individual freshly prepared patients’ plasmas. From the results obtained, the following conclusions may be drawn :The reproducibility of results obtained with manual reading on lyophilized plasmas is satisfactory for all five test procedures. For Simplastin, the reproducibility of values in the range of insufficient anticoagulation is relatively low due to the low discrimination power of the test procedure in the near-normal range (so-called low sensitivity of rabbit brain thromboplastins). The reproducibility of Thrombotest excels as a consequence of its particularly easily discerned coagulation endpoint.The reproducibility of Thrombotest, when tested on freshly prepared plasmas using Schnitger’s semiautomatic coagulometer (a fibrinometer-liJce apparatus), is no longer superior to that of Simplastin A.The constant of proportionality between the coagulation times formed with Simplastin A and Thrombotest was estimated at 0.64.Reconstituted Thrombotest is stable for 24 hours when stored at 4° C, whereas reconstituted Simplastin A is not.The Simplastin A method and Thrombotest seem to be equally sensitive to “activation” of blood coagulation upon storage.

Hardy-Weinberg Testing for Continuous Data

Genetics ◽  
1997 ◽  
Vol 147 (4) ◽  
pp. 1965-1975
Author(s):  
Lauren M McIntyre ◽  
B S Weir
Keyword(s):  
Intraclass Correlation ◽  
Kernel Density ◽  
Variable Number ◽  
Continuous Data ◽  
Test Statistic ◽  
Test Procedures ◽  
Chi Square ◽  
Exact Test ◽  
Chi Square Test ◽  
The Many

Abstract Estimation of allelic and genotypic distributions for continuous data using kernel density estimation is discussed and illustrated for some variable number of tandem repeat data. These kernel density estimates provide a useful representation of data when only some of the many variants at a locus are present in a sample. Two Hardy-Weinberg test procedures are introduced for continuous data: a continuous chi-square test with test statistic TCCS and a test based on Hellinger's distance with test statistic TCCS. Simulations are used to compare the powers of these tests to each other and to the powers of a test of intraclass correlation TIC, as well as to the power of Fisher's exact test TFET applied to discretized data. Results indicate that the power of TCCS is better than that of THD but neither is as powerful as TFET. The intraclass correlation test does not perform as well as the other tests examined in this article.

scholarly journals Experimental Testing of a Size-Exclusion Chromatography Method Used for Evaluation of Molecular Parameters of Equine Anti-Ebola Immunoglobulin

2019 ◽  
Vol 19 (4) ◽  
pp. 261-267
Author(s):  
Е. Yu. Mishalova ◽  
E. V. Gordeev ◽  
V. N. Lebedev ◽  
S. A. Melnikov ◽  
S. A. Nimirskaya ◽  
...  
Keyword(s):  
Specific Activity ◽  
Experimental Testing ◽  
Horse Serum ◽  
Test Procedure ◽  
Size Exclusion ◽  
Array Detector ◽  
Test Procedures ◽  
Molecular Parameters ◽  
Hplc System

Haemorrhagic fever caused by the Ebola virus is a highly hazardous infectious disease with a mortality rate of 50– 90 %. Heterologous immunoglobulins with a high virus-neutralizing titer are an important element of the WHO-endorsed set of measures for emergency prevention and treatment of the disease. Specific activity of these products is largely determined by their fractional composition, and, in particular, by molecular mass distribution (MMD). The size-exclusion-high-performance liquid chromatography (SEC-HPLC) has traditionally been used for determination of the MMD of the target protein in human immunoglobulin-based products. The use of this method for evaluation of molecular parameters of heterologous immunoglobulin requires confirmation of its specificity, accuracy and precision, and establishment of the chromatographic system suitability criteria in the context of a new test object.The aim of the study was to test the applicability of the SEC-HPLC method to the assessment of molecular parameters of anti-Ebola immunoglobulin derived from horse serum.Materials and methods: three batches of purified equine anti-Ebola immunoglobulin were used in the study. Normal equine and human immunoglobulins of the IgG isotype were used as reference standards. The HPLC test procedures described in the European Pharmacopoeia 9.6 and State Pharmacopoeia of the Russian Federation, 14th ed., were used for determination of monomers and other immunoglobulin fractions. An Agilent 1260 Infinity (Agilent, USA) HPLC system with a diode array detector and an Agilent Bio SEC-3 HPLC column were used for quality evaluation of the tested products.Results: the resolution factor between IgG monomer and dimer peaks (1.69 and 2.10), and the chromatographic column efficiency (>2000) make it possible to use the SEC-HPLC system for evaluation of molecular parameters of heterologous immunoglobulin. The study demonstrated reproducibility of the test procedure.Conclusions: the study confirmed the applicability of the SEC-HPLC procedure for evaluation of molecular parameters of anti-Ebola immunoglobulin derived from horse serum. It demonstrated the compliance of the purified immunoglobulin to the national and international quality requirements in terms of «Molecular parameters».

Test procedure and sample size determination for a proportion study using a double-sampling scheme with two fallible classifiers

2017 ◽  
Vol 28 (4) ◽  
pp. 1019-1043 ◽  
Author(s):  
Shi-Fang Qiu ◽  
Xiao-Song Zeng ◽  
Man-Lai Tang ◽  
Wai-Yin Poon
Keyword(s):  
Sample Size ◽  
Null Hypothesis ◽  
Test Procedure ◽  
Sample Size Determination ◽  
Double Sampling ◽  
Score Statistic ◽  
Wald Statistic ◽  
Test Procedures ◽  
Practical Applications ◽  
Logit Transformation

Double sampling is usually applied to collect necessary information for situations in which an infallible classifier is available for validating a subset of the sample that has already been classified by a fallible classifier. Inference procedures have previously been developed based on the partially validated data obtained by the double-sampling process. However, it could happen in practice that such infallible classifier or gold standard does not exist. In this article, we consider the case in which both classifiers are fallible and propose asymptotic and approximate unconditional test procedures based on six test statistics for a population proportion and five approximate sample size formulas based on the recommended test procedures under two models. Our results suggest that both asymptotic and approximate unconditional procedures based on the score statistic perform satisfactorily for small to large sample sizes and are highly recommended. When sample size is moderate or large, asymptotic procedures based on the Wald statistic with the variance being estimated under the null hypothesis, likelihood rate statistic, log- and logit-transformation statistics based on both models generally perform well and are hence recommended. The approximate unconditional procedures based on the log-transformation statistic under Model I, Wald statistic with the variance being estimated under the null hypothesis, log- and logit-transformation statistics under Model II are recommended when sample size is small. In general, sample size formulae based on the Wald statistic with the variance being estimated under the null hypothesis, likelihood rate statistic and score statistic are recommended in practical applications. The applicability of the proposed methods is illustrated by a real-data example.

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