scholarly journals Multiple Comparison with a Control Using Step-down Procedure

2020 ◽  
Vol 8 (2) ◽  
Author(s):  
Bumrungsak Phuenaree ◽  
Suttinee Kaewtaworn
Keyword(s):  
Error Rate ◽  
Single Step ◽  
Multiple Comparison ◽  
Control Group ◽  
Test Statistics ◽  
Familywise Error Rate ◽  
Dunnett Test ◽  
The Family ◽  
Bonferroni Test ◽  
Step Down

The purpose of this research was to compare the efficiency of single-step procedures and the step-down procedures in order to test for multiple comparison with a control group. Four tests; Dunnett test, Step-down Dunnett test, Bonferroni test and Bonferroni-Holm test, was considered. The performance of these tests was evaluated in terms of the family wise error rate, any-pair power and all-pairs power. A Monte Carlo simulation was performed with repeated 10,000 times. The results showed that the familywise error rate of all test statistics closed to the nominal level. The empirical power of step-down procedures were higher than the single-step procedures, and the step-down Dunnett test gave the highest power.

scholarly journals Multiple Testing. Part II. Step-Down Procedures for Control of the Family-Wise Error Rate

2004 ◽  
Vol 3 (1) ◽  
pp. 1-33 ◽  
Author(s):  
Mark J. van der Laan ◽  
Sandrine Dudoit ◽  
Katherine S. Pollard
Keyword(s):  
Error Rate ◽  
Multiple Testing ◽  
Type I Error ◽  
Null Distribution ◽  
Type I ◽  
Test Statistics ◽  
P Values ◽  
Family Wise Error Rate ◽  
The Family ◽  
Step Down

The present article proposes two step-down multiple testing procedures for asymptotic control of the family-wise error rate (FWER): the first procedure is based on maxima of test statistics (step-down maxT), while the second relies on minima of unadjusted p-values (step-down minP). A key feature of our approach is the characterization and construction of a test statistics null distribution (rather than data generating null distribution) for deriving cut-offs for these test statistics (i.e., rejection regions) and the resulting adjusted p-values. For general null hypotheses, corresponding to submodels for the data generating distribution, we identify an asymptotic domination condition for a null distribution under which the step-down maxT and minP procedures asymptotically control the Type I error rate, for arbitrary data generating distributions, without the need for conditions such as subset pivotality. Inspired by this general characterization, we then propose as an explicit null distribution the asymptotic distribution of the vector of null value shifted and scaled test statistics. Step-down procedures based on consistent estimators of the null distribution are shown to also provide asymptotic control of the Type I error rate. A general bootstrap algorithm is supplied to conveniently obtain consistent estimators of the null distribution.

Fast closed testing for exchangeable local tests

Biometrika ◽  
2020 ◽  
Vol 107 (3) ◽  
pp. 761-768 ◽  
Author(s):  
E Dobriban
Keyword(s):  
Error Rate ◽  
Multiple Testing ◽  
Exact Algorithm ◽  
Multiple Hypothesis Testing ◽  
Test Statistics ◽  
Familywise Error Rate ◽  
Closure Principle ◽  
Worst Case ◽  
Higher Criticism ◽  
False Discovery

Summary Multiple hypothesis testing problems arise naturally in science. This note introduces a new fast closed testing method for multiple testing which controls the familywise error rate. Controlling the familywise error rate is state-of-the-art in many important application areas and is preferred over false discovery rate control for many reasons, including that it leads to stronger reproducibility. The closure principle rejects an individual hypothesis if all global nulls of subsets containing it are rejected using some test statistics. It takes exponential time in the worst case. When the tests are symmetric and monotone, the proposed method is an exact algorithm for computing the closure, is quadratic in the number of tests, and is linear in the number of discoveries. Our framework generalizes most examples of closed testing, such as Holm’s method and the Bonferroni method. As a special case of the method, we propose the Simes and higher criticism fusion test, which is powerful both for detecting a few strong signals and for detecting many moderate signals.

scholarly journals Pairwise Multiple Comparison Adjustment Procedure for Survival Functions with Right-Censored Data

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Ertugrul Colak ◽  
Hulya Ozen ◽  
Busra Emir ◽  
Setenay Oner
Keyword(s):  
Error Rate ◽  
Survival Data ◽  
Type I Error ◽  
Multiple Comparison ◽  
Type I ◽  
Familywise Error Rate ◽  
Data Set ◽  
Right Censored Data ◽  
Adjustment Procedure ◽  
Liver Transplant Waiting List

The aim of this study is to propose a new pairwise multiple comparison adjustment procedure based on Genz’s numerical computation of probabilities from a multivariate normal distribution. This method is applied to the results of two-sample log-rank and weighted log-rank statistics where the survival data contained right-censored observations. We conducted Monte Carlo simulation studies not only to evaluate the familywise error rate and power of the proposed procedure but also to compare the procedure with conventional methods. The proposed method is also applied to the data set consisting of 815 patients on a liver transplant waiting list from 1990 to 1999. It was found that the proposed method can control the type I error rate, and it yielded similar power as Tukey’s and high power with respect to the other adjustment procedures. In addition to having a straightforward formula, it is easy to implement.

scholarly journals Multiple Testing. Part I. Single-Step Procedures for Control of General Type I Error Rates

2004 ◽  
Vol 3 (1) ◽  
pp. 1-69 ◽  
Author(s):  
Sandrine Dudoit ◽  
Mark J. van der Laan ◽  
Katherine S. Pollard
Keyword(s):  
Error Rate ◽  
Multiple Testing ◽  
Type I Error ◽  
Null Distribution ◽  
Error Rates ◽  
Single Step ◽  
Type I ◽  
Test Statistics ◽  
Testing Procedures ◽  
Multiple Testing Procedures

The present article proposes general single-step multiple testing procedures for controlling Type I error rates defined as arbitrary parameters of the distribution of the number of Type I errors, such as the generalized family-wise error rate. A key feature of our approach is the test statistics null distribution (rather than data generating null distribution) used to derive cut-offs (i.e., rejection regions) for these test statistics and the resulting adjusted p-values. For general null hypotheses, corresponding to submodels for the data generating distribution, we identify an asymptotic domination condition for a null distribution under which single-step common-quantile and common-cut-off procedures asymptotically control the Type I error rate, for arbitrary data generating distributions, without the need for conditions such as subset pivotality. Inspired by this general characterization of a null distribution, we then propose as an explicit null distribution the asymptotic distribution of the vector of null value shifted and scaled test statistics. In the special case of family-wise error rate (FWER) control, our method yields the single-step minP and maxT procedures, based on minima of unadjusted p-values and maxima of test statistics, respectively, with the important distinction in the choice of null distribution. Single-step procedures based on consistent estimators of the null distribution are shown to also provide asymptotic control of the Type I error rate. A general bootstrap algorithm is supplied to conveniently obtain consistent estimators of the null distribution. The special cases of t- and F-statistics are discussed in detail. The companion articles focus on step-down multiple testing procedures for control of the FWER (van der Laan et al., 2004b) and on augmentations of FWER-controlling methods to control error rates such as tail probabilities for the number of false positives and for the proportion of false positives among the rejected hypotheses (van der Laan et al., 2004a). The proposed bootstrap multiple testing procedures are evaluated by a simulation study and applied to genomic data in the fourth article of the series (Pollard et al., 2004).

scholarly journals SDMinP: a program to control the family wise error rate using step-down minP adjusted P-values

2005 ◽  
Vol 21 (14) ◽  
pp. 3183-3184 ◽  
Author(s):  
M. Obreiter ◽  
C. Fischer ◽  
J. Chang-Claude ◽  
L. Beckmann
Keyword(s):  
Error Rate ◽  
P Values ◽  
Family Wise Error Rate ◽  
The Family ◽  
Step Down

Faktor-Faktor Determinan yang melatar belakangi Kehamilan Remaja di Desa Pandansari Kecamatan Poncokusumo Kabupaten Malang

2020 ◽  
Vol 7 (2) ◽  
pp. 247-255
Author(s):  
Maria Magdalena Setyaningsih ◽  
Emy Sutiyarsih
Keyword(s):  
Sex Education ◽  
Teen Pregnancy ◽  
Teenage Pregnancy ◽  
Well Being ◽  
Case Control ◽  
Control Group ◽  
Case Group ◽  
The Family ◽  
History Of ◽  
First Time

Kehamilan remaja adalah kehamilan yang terjadi pada remaja berusia kurang dari 20 tahunan. Kehamilan remaja memberikan banyak kerugian bagi kesehatan, mental dan psikologis, kesejahteraan ekonomi dan peluang karier, kemiskinan dan prospek kehidupan masa depan remaja. Tujuan penelitian mengidentifikasi faktor determinan yang melatarbelakangi terjadinya kehamilan remaja. Jenis penelitian adalah penelitian analitik kategorik jenis survei kuantitatif dengan desain case control. Populasi semua perempuan yang bertempat tinggal di wilayah dusun Wonosari, Sukosari, dan Krajan Pandansari dan pernah/sedang hamil pertama kali pada usia kurang dari 20 tahun. Teknik pengambilan sampel cluster random sampling besar sampel 73. Berdasarkan hasil model akhir analisis multivariat, diketahui bahwa variabel pendidikan, riwayat kehamilan remaja pada keluarga dan usia menikah merupakan variabel yang berhubungan dengan kejadian kehamilan remaja setelah dikontrol oleh variabel akses informasi, responden berpendidikan rendah memiliki peluang 20,8 kali lebih tinggi, responden yang memiliki riwayat kehamilan remaja pada keluarga memiliki peluang 14,9 kali lebih tinggi, responden yang menikah pada usia <20 tahun memiliki peluang 12,1 kali lebih tinggi, responden dengan pemahaman yang kurang baik terkait penggunaan kondom memiliki peluang 5,9 kali lebih tinggi untuk terjadi kehamilan remaja. Oleh karena itu perlu dibangun karakter buiding, sosial karakter suport untuk para ibu remaja dan keluarga sehingga terbangun interaksi yang baik dalam keluarga yang dilandasi dengan pendidikan dan pemahaman yang baik tentang Pendidikan seksualitas. Teen pregnancy is a pregnancy that occurs in adolescents aged less than 20 years old. Teen pregnancy provides many disadvantages for health, mental, psychological, economic well-being, career opportunities, poverty, and the future life. The aim of the study was to identify the determinants underlying teen pregnancy incidence. This study was a quantitative study with categorical analytic method. The study design used a case control with two comparison groups. The groups were control group and case group. The population in this study was all women who lived in the Wonosari, Sukosari, and Krajan Pandansari district and had or were pregnant for the first time at the age of less than 20 years old. Seventy three respondents were recruited using cluster sampling technique. The case group consists of women who were or had pregnant for the first time at the age of less than 20 years old and their children are currently aged ≤ 1 years old. The control group consists of women who were pregnant for the first time at the age of > 20 years old. The data was collected using a questionnaire. The findings showed that education, history of teen pregnancy in family and the age of marriage were related to the incidence of teen pregnancy after being controlled by information access. Low-educated respondents had 20.8 times higher chance of experiencing teen pregnancy; respondents with a history of teen pregnancy in the family had 4.9 times higher chance of experiencing teen pregnancy; respondents who were married at the age of < 20 years old had 12.1 times higher chance of experiencing teen pregnancy; respondents with poor understanding of condom use had 5.9 times higher chance of teenage pregnancy. In conclusion, the findings suggest to build good interactions in the family based on education and a good understanding of sex education.

The effect of brain vitalization activity on dementia incidence in elderly at Budi Luhur Nursing Home of Yogyakarta, Kasongan, Bantul

2020 ◽  
Vol 1 (3) ◽  
pp. 43-50
Author(s):  
Firstyono Miftahul Aziz ◽  
Suratini Suratini
Keyword(s):  
Nursing Home ◽  
The Elderly ◽  
Control Group ◽  
P Value ◽  
Sampling System ◽  
Randomized Sampling ◽  
Care For The Elderly ◽  
Dementia Incidence ◽  
The Family ◽  
The Impact

For some people, dementia is considered as a disease that is common in elderly, regardless the impact of dementia. Taking care for the elderly with dementia brings stress for the family. It can cause and increase the family burden. Brain vitalization gymnastics is one of the methods to improve memory. The study aims to investigate the effect of brain vitalization activity on dementia incidence in elderly at Budi Luhur Nursing Home of Yogyakarta. The study used Quasi Experimental with Pretest-Posttest control group and randomized sampling system. The samples were taken randomly as many as 26 respondents and were divided into two groups namely 13 respondents of experimental group and 13 respondents of control group. The statistical test used Wilcoxon Match Pairs Test. The result showed that Wilcoxon Match pairs test obtained p value 0,003, which is smaller than 0,005. There is an effect of brain vitalization activity on dementia incidence in elderly at Budi Luhur Nursing Home of Yogyakarta

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