Edmond Lui

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Sarva Mangala Praveena

UPM - Universiti Putra Malaysia

Jayjit Majumdar

University of Kalyani

Francesco Stingo

Università degli Studi di Firenze (University of Florence)

Ulla Sovio

London School of Hygiene & Tropical Medicine

Remo Caponi

University of Cologne

Jeffrey Townsend

Yale University

Fatma AYDINOĞLU

Gebze Technical University

Chuan-Chao Wang

Xiamen University

Srinivasa Rao Gadde

The University of Dodoma, Tanzania

E.i.abdul Sathar

University of Kerala

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Papers by Edmond Lui

Test Equaltiy Between Three Treatments Under an Incomplete Block Crossover Design

Journal of biopharmaceutical statistics, Jan 6, 2014

ABSTRACT Under a random effects linear additive risk model, we compare two experimental treatment... more ABSTRACT Under a random effects linear additive risk model, we compare two experimental treatments with a placebo in continuous data under an incomplete block crossover trial. We develop three test procedures for simultaneously testing equality between two experimental treatments and a placebo, as well as interval estimators for the mean difference between treatments. We apply Monte Carlo simulations to evaluate the performance of these test procedures and interval estimators in a variety of situations. We note that the bivariate test procedure accounting for the dependence structure based on the F-test is preferable to the other two procedures when there is only one of the two experimental treatments has a non-zero effect versus the placebo. We note further that when the effects of the two experimental treatments versus a placebo are in the same relative directions and are approximately of equal magnitude, the summary test procedure based on a simple average of two weighted-least-squares (WLS) estimators can outperform the other two procedures with respect to power. When one of the two experimental treatments has a relatively large effect versus the placebo, the univariate test procedure with using Bonferroni&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s equality can be still of use. Finally, we use the data about the forced expiratory volume in 1 second (FEV1) readings taken from a double-blind crossover trial comparing two different doses of formoterol with a placebo to illustrate the use of test procedures and interval estimators proposed here.

A model-based estimate of the mean incubation period for AIDS in homosexual men

Science, 1988

Because of the difficulty in identifying the date of exposure to type 1 of the human immunodefici... more Because of the difficulty in identifying the date of exposure to type 1 of the human immunodeficiency virus (HIV-1) infection in persons other than transfusion recipients, studies of the incubation periods for acquired immunodeficiency syndrome (AIDS) have been limited. When data from a cohort of 84 homosexual and bisexual men that provided the information to determine the years of conversion of sera infected with HIV-1 were analyzed, a model for the proportion likely to develop AIDS and the incubation period for AIDS in homosexual men could be derived. The maximum likelihood estimate for the proportion of infected homosexual men developing AIDS is 0.99 (90% confidence interval ranging from 0.38 to 1). Furthermore, the maximum likelihood estimate for the mean incubation period for AIDS in homosexual men is 7.8 years (90% confidence interval ranging from 4.2 years to 15.0 years), which is close to the estimate of 8.2 years for adults developing transfusion-associated AIDS.

Acquired Immunodeficiency Syndrome (AIDS) Associated with Transfusions

New England Journal of Medicine, 1984

intubation was attempted in the field, were studied. Field teams were limited to three attempts a... more intubation was attempted in the field, were studied. Field teams were limited to three attempts at intubation, with the exception of six cases in which the EMS physician authorized four or more attempts. Of the 779 patients, 701 (90.0%) were intubated successfully --58% on the first attempt, 26% on the second attempt, and 6% on the third attempt. There were 74 reported and observed complications in 10% of the 779 patients. These included 42 prolonged attempts at intubation (> 45 seconds), 11 esophageal placements (three of which were unrecognized), three right mainstem placements, seven vomiting episodes during intubation, three patients with soft tissue trauma, and three patients with dental trauma. The success rate rose to more than 94% toward the end of the study as the experience level of paramedics increased. The authors concluded that endotracheal intubation of deeply comatose patients is a field procedure safely and skillfully performed by welltrained and monitored paramedical personnel with a minimum of complications.

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A model-based approach to characterize the incubation period of paediatric transfusion-associated acquired immunodeficiency syndrome

Statistics in Medicine, 1988

Traditional statistics, such as the average, currently provide a misleading statistical descripti... more Traditional statistics, such as the average, currently provide a misleading statistical description of the incubation periods of paediatric transfusion-associated acquired immunodeficiency syndrome (TA-AIDS). Two types of length-biased sampling, left censoring and right censoring, occur in the 37 cases diagnosed before 1986 and reported to the Centers for Disease Control by 15 September 1986. To correct for these problems, we propose a truncated Weibull distribution with use of a maximum likelihood technique. This approach suggests that the mean incubation period of paediatric TA-AIDS cases is 2.4 years with a 90 per cent confidence interval ranging from 1.5 years to 7.2 years. The mode is 1.25 years. These estimates are much shorter than those recently published for adults, therefore the success of TA-AIDS prevention strategies may be seen sooner in the paediatric age group.

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Notes on interval estimation of the attributable risk in cross-sectional sampling

Statistics in Medicine, 2001

The attributable risk (AR) is probably the most useful and commonly used epidemiologic index to m... more The attributable risk (AR) is probably the most useful and commonly used epidemiologic index to measure the importance of a risk factor in public health issues. This paper focuses the discussion on interval estimation of the AR in cross-sectional studies and compares the finite-sample performance of five asymptotic interval estimators of the AR by calculating the coverage probability and the average length in a variety of situations. This paper notes that the coverage probability of the two interval estimators proposed by Leung and Kupper, including the one that combines the interval estimator on the basis of Wald's test statistic, can be substantially less than the desired confidence level when the underlying risk ratio equals 1. As long as the sample size is reasonably large (⩾100) and the probability of exposure is moderate (⩾0.20), the interval estimator suggested by Fleiss can consistently perform well with respect to the coverage probability in a variety of situations considered here. However, using this interval estimator tends to generally lose efficiency. This paper also finds that with respect to the coverage probability, the interval estimator using Fieller's theorem is generally preferable to the interval estimator on the basis of Wald's test statistic when the prevalence rate ratio (RR) between the exposure and the non-exposure groups is ⩾2. Finally, this paper notes that if we know that the underlying parameter RR is large (⩾4) and the probability of exposure is not small (⩾0.05), the interval estimator suggested by Leung and Kupper will probably be preferable to all the other estimators considered here. Copyright © 2001 John Wiley & Sons, Ltd.

Sample Size Determination for Repeated Measurements in Bioequivalence Test

Journal of Pharmacokinetics and Pharmacodynamics, 1997

When the measurement of outcome is unreliable or the cost of obtaining an additional subject is r... more When the measurement of outcome is unreliable or the cost of obtaining an additional subject is relatively high compared to the cost of obtaining an additional measurement from the same subject, it may be desirable to consider taking more than one measurement per subject to increase power or to minimize the cost in a clinical trial. When each subject in two comparison groups has a fixed number of repeated measurements, this paper develops an asymptotic procedure to calculate the number of subjects per group required to achieve a given power for an α-level bioequivalence test. Furthermore, Monte Carlo simulation is used to evaluate the accuracy of the approximate sample size calculation procedure and a brief discussion on how to determine the optimal number of repeated measurements is included.

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Exact equivalence test for risk ratio and its sample size determination under inverse sampling

Statistics in Medicine, 1997

When data are dichotomous, this paper notes the utility of inverse sampling in establishing equiv... more When data are dichotomous, this paper notes the utility of inverse sampling in establishing equivalence with respect to the risk ratio. This paper develops an exact equivalence test that accounts for the risk ratio under inverse sampling and further discusses the relationship between the exact equivalence test and the exact conditional confidence limits. Also included are an exact and two asymptotic procedures for calculation of the minimum required number of index subjects for a desired power 1--beta at a given alpha-level. Finally, this paper provides a table that summarizes the minimum required number of index subjects for powers equal to 0.90 and 0.80 in application of the proposed exact equivalence test at 0.05-level in a variety of situations.

Sample sizes for repeated measurements in dichotomous data

Statistics in Medicine, 1991

When the measurement of outcome varies within studied subjects and the cost of additional subject... more When the measurement of outcome varies within studied subjects and the cost of additional subjects is high, taking more than one measurement for each subject constitutes a useful alternative to increase the power or to reduce the total cost of the study. In this paper, I present sample size formulae for repeated measurements in dichotomous data under different situations. I also discuss optimal sample allocation for repeated measurements.

Interval estimation of the difference in proportions under m-to-one matching

Statistics in medicine, Jan 15, 2005

When the number of potential controls is large relative to the number of available cases, or when... more When the number of potential controls is large relative to the number of available cases, or when little e ort needs to be expended in collecting the relevant information on the controls, we often apply multiple matching to attain the validity or increase the e ciency of our inference in epidemiological studies. In this paper, we focus interval estimation on the di erence in proportions for m-to-one matching. We consider four asymptotic interval estimators, including the estimator directly using the Mantel-Haenszel (MH) point estimator, the estimator using the tanh −1 (x) transformation, the estimator derived from the Cochran-Mantel-Haenszel (CMH) test statistic, and the estimator derived from the quadratic inequality developed in this paper. To evaluate and compare the performance of these estimators, we employ Monte Carlo simulation. We ÿnd that the estimator directly using the MH estimator can have the coverage probability less than the desired conÿdence level when the number of matched sets is small. We note that the estimator derived from the quadratic inequality can perform well when the underlying di erence is close to 0 even for a small number of matched sets. However, this estimator tends to have the coverage probability less than the desired conÿdence level as well when the underlying di erence in proportions is large. By contrast, the estimator using the CMH statistic tends to have the coverage probability larger than the desired conÿdence level when the underlying di erence is small. We also ÿnd that the estimator using the tanh −1 (x) transformation consistently outperforms the interval estimator directly using the MH estimator. We use the data regarding the association between induced abortions and ectopic pregnancy to illustrate the use of these estimators.

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A semi-parametric approach to the frequency of occurrence under a simple crossover trial

Statistical methods in medical research, Jan 23, 2012

To analyze the frequency of occurrence for an event of interest in a crossover design, we propose... more To analyze the frequency of occurrence for an event of interest in a crossover design, we propose a semi-parametric approach. We develop two point estimators and four interval estimators in closed forms for the treatment effect under a random effects multiplicative risk model. Using Monte Carlo simulations, we evaluate these estimators and compare the four interval estimators with the classical interval estimator suggested elsewhere in a variety of situations. We note that the point estimator using the ratio of two arithmetic averages of mean frequencies under a multiplicative risk model can be comparable to the point estimator using the ratio of two geometric averages of mean frequencies. We note that as long as the number of patients per group is large, all the four interval estimators developed here can perform well. We also note that the classical interval estimator derived under the commonly assumed Poisson distribution for the frequency data can be conservative and lose precision if the Poisson distribution assumption is violated. We use a double-blind randomized crossover trial comparing salmeterol with a placebo in exacerbations of asthma to illustrate the practical use of these estimators.

Analysis of Poisson frequency data under a simple crossover trial

Statistical methods in medical research, Jan 16, 2012

When the frequency of occurrence for an event of interest follows a Poisson distribution, we deve... more When the frequency of occurrence for an event of interest follows a Poisson distribution, we develop asymptotic and exact procedures for testing non-equality, non-inferiority and equivalence, as well as asymptotic and exact interval estimators for the ratio of mean frequencies between two treatments under a simple crossover design. Using Monte Carlo simulations, we evaluate the performance of these test procedures and interval estimators in a variety of situations. We note that all asymptotic test procedures developed here can generally perform well with respect to Type I error and can be preferable to the exact test procedure with respect to power if the number of patients per group is moderate or large. We further find that in these cases the asymptotic interval estimator with the logarithmic transformation can be more precise than the exact interval estimator without sacrificing the accuracy with respect to the coverage probability. However, the exact test procedure and exact interval estimator can be of use when the number of patients per group is small. We use a double-blind randomized crossover trial comparing salmeterol with a placebo in exacerbations of asthma to illustrate the practical use of these estimators.

Notes on testing noninferiority in multivariate binary data under the matched-pair design

Statistical methods in medical research, Jan 12, 2013

Since therapeutic efficacy is often measured by multiple endpoints, it will be of use if one can ... more Since therapeutic efficacy is often measured by multiple endpoints, it will be of use if one can incorporate the information on various variables of response into procedures for testing noninferiority to improve power of a univariate test procedure for each individual variable. On the basis of the proposed mixed effects logistic regression model for multivariate binary data under the matched-pairs design, we develop procedures for testing noninferiority with respect to the odds ratio in multivariate binary data under the matched-pair design. We discuss use of Bonferroni&amp;amp;amp;amp;amp;amp;#39;s and Scheffe&amp;amp;amp;amp;amp;amp;#39;s methods to control the inflation in Type I error due to multiple tests. We further employ Monte Carlo simulation to evaluate and compare the performance of these test procedures. Finally, we use the data taken from a crossover clinical trial that monitored several adverse events of an antidepressive drug to illustrate the use of test procedures derived here.

Notes on testing noninferiority in ordinal data under the parallel groups design

Journal of biopharmaceutical statistics, 2013

When testing the noninferiority of an experimental treatment to a standard (or control) treatment... more When testing the noninferiority of an experimental treatment to a standard (or control) treatment in a randomized clinical trial (RCT), we may come across the outcomes of patient response on an ordinal scale. We focus our discussion on testing noninferiority in ordinal data for an RCT under the parallel groups design. We develop simple test procedures based on the generalized odds ratio (GOR). We note that these test procedures not only can account for the information on the order of ordinal responses without assuming any specific parametric structural model, but also can be independent of any arbitrarily subjective scoring system. We further develop sample size determination based on the test procedure using the GOR. We apply Monte Carlo simulation to evaluate the performance of these test procedures and the accuracy of sample size calculation formula proposed here in a variety of situations. Finally, we employ the data taken from a trial comparing once-daily gatifloxican with three-times-daily co-amoxiclav in the treatment of community-acquired pneumonia to illustrate the use of these test procedures and sample size calculation formula.

Notes on testing equality and interval estimation in Poisson frequency data under a three-treatment three-period crossover trial

Statistical methods in medical research, Jan 17, 2014

When the frequency of event occurrences follows a Poisson distribution, we develop procedures for... more When the frequency of event occurrences follows a Poisson distribution, we develop procedures for testing equality of treatments and interval estimators for the ratio of mean frequencies between treatments under a three-treatment three-period crossover design. Using Monte Carlo simulations, we evaluate the performance of these test procedures and interval estimators in various situations. We note that all test procedures developed here can perform well with respect to Type I error even when the number of patients per group is moderate. We further note that the two weighted-least-squares (WLS) test procedures derived here are generally preferable to the other two commonly used test procedures in the contingency table analysis. We also demonstrate that both interval estimators based on the WLS method and interval estimators based on Mantel-Haenszel (MH) approach can perform well, and are essentially of equal precision with respect to the average length. We use a double-blind randomized three-treatment three-period crossover trial comparing salbutamol and salmeterol with a placebo with respect to the number of exacerbations of asthma to illustrate the use of these test procedures and estimators.

Test equality between two binary screening tests with a confirmatory procedure restricted on screen positives

Journal of biopharmaceutical statistics, 2015

In studies of screening accuracy, we may commonly encounter the data in which a confirmatory proc... more In studies of screening accuracy, we may commonly encounter the data in which a confirmatory procedure is administered to only those subjects with screen positives for ethical concerns. We focus our discussion on simultaneously testing equality of sensitivity and specificity between two binary screening tests when only subjects with screen positives receive the confirmatory procedure. We develop four asymptotic test procedures and one exact test procedure. We derive sample size calculation formula for a desired power of detecting a difference at a given nominal [Formula: see text]-level. We employ Monte Carlo simulation to evaluate the performance of these test procedures and the accuracy of the sample size calculation formula developed here in a variety of situations. Finally, we use the data obtained from a study of the prostate-specific-antigen test and digital rectal examination test on 949 Black men to illustrate the practical use of these test procedures and the sample size calculation formula.

Testing equality and interval estimation in binary responses when high dose cannot be used first under a three-period crossover design

Journal of biopharmaceutical statistics, 2015

When comparing two doses of a new drug with a placebo, we may consider using a crossover design s... more When comparing two doses of a new drug with a placebo, we may consider using a crossover design subject to the condition that the high dose cannot be administered before the low dose. Under a random-effects logistic regression model, we focus our attention on dichotomous responses when the high dose cannot be used first under a three-period crossover trial. We derive asymptotic test procedures for testing equality between treatments. We further derive interval estimators to assess the magnitude of the relative treatment effects. We employ Monte Carlo simulation to evaluate the performance of these test procedures and interval estimators in a variety of situations. We use the data taken as a part of trial comparing two different doses of an analgesic with a placebo for the relief of primary dysmenorrhea to illustrate the use of the proposed test procedures and estimators.

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

Statistical methods in medical research, Jan 10, 2015

The crossover design can be of use to save the number of patients or improve power of a parallel ... more 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.

Sample size determination for testing nonequality under a three-treatment two-period incomplete block crossover trial

Biometrical journal. Biometrische Zeitschrift, Jan 10, 2015

To reduce the lengthy duration of a crossover trial for comparing three treatments, the incomplet... more To reduce the lengthy duration of a crossover trial for comparing three treatments, the incomplete block design has been often considered. A sample size calculation procedure for testing nonequality between either of the two experimental treatments and a placebo under such a design is developed. To evaluate the performance of the proposed sample size calculation procedure, Monte Carlo simulation is employed. The accuracy of the sample size calculation procedure developed here is demonstrated in a variety of situations. As compared with the parallel groups design, a substantial proportional reduction in the total minimum required sample size in use of the incomplete block crossover design is found. A crossover trial comparing two different doses of formoterol with a placebo on the forced expiratory volume is applied to illustrate the use of the sample size calculation procedure.

A Model-Based Approach for Estimating the Mean Incubation Period of Transfusion-Associated Acquired Immunodeficiency Syndrome

Proceedings of The National Academy of Sciences, 1986

The incubation period, representing the interval between the date of exposure and the date of dia... more The incubation period, representing the interval between the date of exposure and the date of diagnosis, can be firmly ascertained in transfusion-associated cases of acquired immunodeficiency syndrome (AIDS). However, because the observation period of all transfusion-infected persons may be short compared with the average incubation period for AIDS, many cases with long incubation periods have not yet been diagnosed. Thus, the simple average of 2.6 years tends to underestimate the true mean. To correct for this underestimation bias, we assumed that the underlying distribution of the incubation periods is a member of a broad class of probability densities. Then, by maximum likelihood techniques, the mean incubation period for transfusion-associated AIDS was estimated to be 4.5 years, with the 90% confidence interval ranging from 2.6 to 14.2 years. The long incubation period has important consequences for infected individuals and implications for public health intervention and prevention policy.

Test Homogeneity of Odds Ratio in a Randomized Clinical Trial with Noncompliance

Journal of Biopharmaceutical Statistics, 2009

The odds ratio (OR) has been recommended to measure the relative treatment effect in therapeutic ... more The odds ratio (OR) has been recommended to measure the relative treatment effect in therapeutic equivalence or meta-analysis. When controlling the confounding effect due to strata formed by centers (or trials) on patients&amp;amp;amp;amp;#39; response in a multicenter study (or a meta-analysis), we commonly employ stratified analysis and obtain a summary estimate of the treatment effect. In practice, it is not uncommon to come across data in which there are patients not complying with their assigned treatment. To avoid obtaining a misleading summary estimate due to overlooking the interaction between the stratum and treatment effects as well as the selection bias from noncompliance, it is important to develop test statistics accounting for noncompliance for testing the homogeneity of the OR across strata. In this article, we develop five asymptotic test statistics and employ Monte Carlo simulation to evaluate the performance of these statistics in a variety of situations. We note that the weighted-least-squares (WLS) test statistic can be liberal when the number of strata is moderate or large (&amp;amp;amp;amp;gt;/=5). We find that the logarithmic transformation of the WLS (LWLS) test statistic, the squared-root transformation of the LWLS (SLWLS) test statistic, and Fisher&amp;amp;amp;amp;#39;s logarithmic transformation of LWLS (LLWLS) test statistic can perform well with respect to Type I error in all the situations considered here. We further find that the Z-transformation of LWLS (ZLWLS) test statistic can be liberal when the number of strata is small or moderate. We note that the LWLS test statistic is likely preferable to the others for a small number of strata, while the ZLWLS test statistic can be the best for a moderate or large number of strata. Finally, we use the data taken from a multiple-risk-factor intervention trial to illustrate the use of these test statistics.

Test Equaltiy Between Three Treatments Under an Incomplete Block Crossover Design

Journal of biopharmaceutical statistics, Jan 6, 2014

A model-based estimate of the mean incubation period for AIDS in homosexual men

Science, 1988

Acquired Immunodeficiency Syndrome (AIDS) Associated with Transfusions

New England Journal of Medicine, 1984

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A model-based approach to characterize the incubation period of paediatric transfusion-associated acquired immunodeficiency syndrome

Statistics in Medicine, 1988

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Notes on interval estimation of the attributable risk in cross-sectional sampling

Statistics in Medicine, 2001

Sample Size Determination for Repeated Measurements in Bioequivalence Test

Journal of Pharmacokinetics and Pharmacodynamics, 1997

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Exact equivalence test for risk ratio and its sample size determination under inverse sampling

Statistics in Medicine, 1997

Sample sizes for repeated measurements in dichotomous data

Statistics in Medicine, 1991

Interval estimation of the difference in proportions under m-to-one matching

Statistics in medicine, Jan 15, 2005

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A semi-parametric approach to the frequency of occurrence under a simple crossover trial

Statistical methods in medical research, Jan 23, 2012

Analysis of Poisson frequency data under a simple crossover trial

Statistical methods in medical research, Jan 16, 2012

Notes on testing noninferiority in multivariate binary data under the matched-pair design

Statistical methods in medical research, Jan 12, 2013

Notes on testing noninferiority in ordinal data under the parallel groups design

Journal of biopharmaceutical statistics, 2013

Notes on testing equality and interval estimation in Poisson frequency data under a three-treatment three-period crossover trial

Statistical methods in medical research, Jan 17, 2014

Test equality between two binary screening tests with a confirmatory procedure restricted on screen positives

Journal of biopharmaceutical statistics, 2015

Testing equality and interval estimation in binary responses when high dose cannot be used first under a three-period crossover design

Journal of biopharmaceutical statistics, 2015

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

Statistical methods in medical research, Jan 10, 2015

Sample size determination for testing nonequality under a three-treatment two-period incomplete block crossover trial

Biometrical journal. Biometrische Zeitschrift, Jan 10, 2015

A Model-Based Approach for Estimating the Mean Incubation Period of Transfusion-Associated Acquired Immunodeficiency Syndrome

Proceedings of The National Academy of Sciences, 1986

Test Homogeneity of Odds Ratio in a Randomized Clinical Trial with Noncompliance

Journal of Biopharmaceutical Statistics, 2009

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