ANALISIS MULTIVARIAT (UJI HOTELLING’S T2)

2020 ◽  
Author(s):  
Adhar Arifuddin

Salah satu uji statistik multivariat yang sering digunakan adalah Uji Hotelling’s T2. Uji Hotelling’s T2 (Hotelling, 1931) berfungsi untuk melihat perbedaan antara dua kelompok percobaan, yang masing-masing kelompok terdiri dari dua variate atau lebih, dan akan dilakukan analisis statistik pada variate tersebut secara serentak1. Uji Hotelling’s T2 atau statistik T2 pada dua sampel bebas adalah salah satu teknik analisis statistik komparasional multivariat yang digunakan untuk membandingkan dua kelompok sampel yang diteliti. Uji Hotelling’s T2 merupakan statistik multivariat yang menjadi pengembangan uji T dua sampel bebas (Perbedaan mean dua kelompok yang bersifat independen). Perbedaannya terletak pada jumlah variabel dependen. Pada Uji T dua sampel bebas hanya memiliki satu variabel dependen, sedangkan uji Hotelling’s T2 memiliki lebih dari satu variabel dependen2.

2017 ◽  
Vol 14 (1) ◽  
pp. 1
Author(s):  
Hakan Eygü ◽  
M. Suphi Özçomak

The sample of the study was formed using simple random sampling, ranked set sampling, extreme ranked set sampling and median ranked set sampling. At the end of this process, the researcher created Hotelling’s T2 control charts, a multivariate statistical process control method. The performances of SRS, RSS, ERSS and MRSS sampling methods were compared to one another using these control charts. A simulation was performed to see the average run-length values for Hotelling’s T2 control charts, and these findings were also used for the comparison of the sampling performances.At the end of the study, the researcher formed a sample using median ranked set sampling and created the Hotelling’s T2 control chart. As a result of this operation, the researcher found that there was an out-of-control signal in the process, while there was no such signal in other sampling methods. When the average run-length values obtained from Hotelling’s T2 control charts were compared, it was seen that a shift in the process was detected by the ranked set sampling earlier, when compared to other sampling methods. This paper it can be said that the methods used are unique to the literature because they are applied to multivariate data.


2010 ◽  
Vol 21 (05) ◽  
pp. 347-356 ◽  
Author(s):  
Lyndal Carter ◽  
Maryanne Golding ◽  
Harvey Dillon ◽  
John Seymour

Background: With the advent of newborn hearing screening programs, the need to verify the fit of hearing aids in young infants has increased. The recording of cortical auditory evoked potentials (CAEPs) for this purpose is quite feasible, but rapid developmental changes that affect response morphology and the presence of electrophysiological noise can make subjective response detection challenging. Purpose: The purpose of this study was to investigate the effectiveness of an automated statistic versus experienced examiners in detecting the presence of infant CAEPs when stimuli were present and reporting the absence of CAEPs when no stimuli were present. Research Design: A repeated-measures design was used where infant-generated CAEPs were interpreted by examiners and an automated statistic. Study Sample: There were nine male and five female infants (mean age, 12 mo; SD, 3.4) who completed behavioral and electrophysiological testing using speech-based stimuli. Data Collection and Analysis: In total, 87 infant CAEPs were recorded to three sensation levels, 10, 20 and 30 dB relative to the behavioral thresholds and to nonstimulus trials. Three examiners were presented with these responses: (1) “in series,” where waveforms were presented in order of decreasing stimulus presentation levels, and (2) “nonseries,” where waveforms were randomized completely and presented as independent waveforms. The examiners were given no information about the stimulus levels and were asked to determine whether responses to auditory stimulation could be observed and their degree of certainty in making their decision. Data from the CAEP responses were also converted to multiple dependent variables and analyzed using Hotelling's T2. Results from both methods of response detection were analyzed using a repeated measures ANOVA (analysis of variance) and parameters of signal detection theory known as d-prime (d′) and the area under the receiver operating characteristic (ROC) curve. Results: Results showed that as the stimulus level increased, the sensitivity index, d′, increased for both methods of response detection, but neither reached the maximum possible d′ value with a sensation level of 30 dB. The examiners with the greatest experience and Hotelling's T2 were equally sensitive in differentiating the CAEP from noise. Conclusions: Hotelling's T2 appears to detect CAEPs from normal hearing infants at a rate equal to that of an experienced examiner. A clinical instrument that applies Hotelling's T2 on-line, so that the likelihood of response detection can be assessed objectively, should be of particular benefit to the novice or less experienced examiner.


2009 ◽  
Vol 3 (Suppl 7) ◽  
pp. S6 ◽  
Author(s):  
Lianfu Chen ◽  
Ming Zhong ◽  
Wei Chen ◽  
Christopher I Amos ◽  
Ruzong Fan

Author(s):  
Sirasak Sasiwannapong ◽  
Saowanit Sukparungsee ◽  
Piyapatr Busababodhin ◽  
Yupaporn Areepong

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