scholarly journals Bayes Factor Design Analysis: Planning for compelling evidence

2016 ◽  
Author(s):  
Felix D. Schönbrodt ◽  
Eric-Jan Wagenmakers
Keyword(s):  
Data Collection ◽  
Sample Size ◽  
Bayes Factor ◽  
Design Analysis ◽  
Maximum Efficiency ◽  
Misleading Evidence ◽  
Current State ◽  
Weak Evidence ◽  
Factor Design ◽  
Design Analyses

A sizeable literature exists on the use of frequentist power analysis in the null-hypothesis significance testing (NHST) paradigm to facilitate the design of informative experiments. In contrast, there is almost no literature that discusses the design of experiments when Bayes factors (BFs) are used as a measure of evidence. Here we explore Bayes Factor Design Analysis (BFDA) as a useful tool to design studies for maximum efficiency and informativeness. We elaborate on three possible BF designs, (a) a fixed-n design, (b) an open-ended Sequential Bayes Factor (SBF) design, where researchers can test after each participant and can stop data collection whenever there is strong evidence for either H1 or H0, and (c) a modified SBF design that defines a maximal sample size where data collection is stopped regardless of the current state of evidence. We demonstrate how the properties of each design (i.e., expected strength of evi- dence, expected sample size, expected probability of misleading evidence, expected probability of weak evidence) can be evaluated using Monte Carlo simulations and equip researchers with the necessary information to compute their own Bayesian design analyses.

scholarly journals A Tutorial on Bayes Factor Design Analysis Using an Informed Prior

2017 ◽  
Author(s):  
Angelika Stefan ◽  
Quentin Frederik Gronau ◽  
Felix D. Schönbrodt ◽  
Eric-Jan Wagenmakers
Keyword(s):  
Bayes Factor ◽  
Design Analysis ◽  
Target Strength ◽  
Sequential Designs ◽  
Web Based ◽  
Strength Of Evidence ◽  
Misleading Evidence ◽  
Research Designs ◽  
Factor Design ◽  
User Friendly

Well-designed experiments are likely to yield compelling evidence with efficient sample sizes. Bayes Factor Design Analysis (BFDA) is a recently developed methodology that allows researchers to balance the informativeness and efficiency of their experiment (Schönbrodt & Wagenmakers, 2017). With BFDA, researchers can control the rate of misleading evidence but, in addition, they can plan for a target strength of evidence. BFDA can be applied to fixed-N and sequential designs. In this tutorial paper, we provide a tutorial-style introduction to BFDA and generalize the method to informed prior distributions. We also present a user-friendly web-based BFDA application that allows researchers to conduct BFDAs with ease. Two practical examples highlight how researchers can use a BFDA to plan for informative and efficient research designs.

scholarly journals Probability that p-value provides misleading evidence cannot be controlled by sample size

2017 ◽  
Author(s):  
Marian Grendar ◽  
George G Judge
Keyword(s):  
Sample Size ◽  
Bayes Factor ◽  
Statistical Evidence ◽  
Sample Size Determination ◽  
P Value ◽  
Size Determination ◽  
Misleading Evidence

A measure of statistical evidence should permit the sample size determination so that the probability M of obtaining (strong) misleading evidence can be held as low as desired. On this desideratum the p-value fails completely, as it leads either to an arbitrary sample size if M >= 0.01 or no sample size at all, if M < 0.01. Unlike the p-value, the ratio of likelihoods, the ratio of posteriors, as well as the Bayes Factor, permit controlling the probability of misleading evidence by the sample size.

scholarly journals Probability that p-value provides misleading evidence cannot be controlled by sample size

2017 ◽  
Author(s):  
Marian Grendar ◽  
George G Judge
Keyword(s):  
Sample Size ◽  
Bayes Factor ◽  
Statistical Evidence ◽  
Sample Size Determination ◽  
P Value ◽  
Size Determination ◽  
Misleading Evidence

A measure of statistical evidence should permit the sample size determination so that the probability M of obtaining (strong) misleading evidence can be held as low as desired. On this desideratum the p-value fails completely, as it leads either to an arbitrary sample size if M >= 0.01 or no sample size at all, if M < 0.01. Unlike the p-value, the ratio of likelihoods, the ratio of posteriors, as well as the Bayes Factor, permit controlling the probability of misleading evidence by the sample size.

scholarly journals Bayes factor design analysis: Planning for compelling evidence

2017 ◽  
Vol 25 (1) ◽  
pp. 128-142 ◽  
Author(s):  
Felix D. Schönbrodt ◽  
Eric-Jan Wagenmakers
Keyword(s):  
Bayes Factor ◽  
Design Analysis ◽  
Compelling Evidence ◽  
Factor Design

scholarly journals A tutorial on Bayes Factor Design Analysis using an informed prior

2019 ◽  
Vol 51 (3) ◽  
pp. 1042-1058 ◽  
Author(s):  
Angelika M. Stefan ◽  
Quentin F. Gronau ◽  
Felix D. Schönbrodt ◽  
Eric-Jan Wagenmakers
Keyword(s):  
Bayes Factor ◽  
Design Analysis ◽  
Factor Design

FAKTOR PENGETAHUAN YANG MEMPENGARUHI KETERATURAN IBU BALITA DALAM MENGUNJUNGI POSYANDU DI DESA CIPANGERAN KECAMATAN SAGULING KABUPATEN BANDUNG BARAT TAHUN 2017

2018 ◽  
Vol 5 (2) ◽  
pp. 13-20
Author(s):  
Lia Kamila ◽  
Liawati . ◽  
Suci Lailani Alipah
Keyword(s):  
Public Health ◽  
Data Collection ◽  
Sample Size ◽  
Health Center ◽  
Analytical Method ◽  
Random Sampling ◽  
Research Method ◽  
Cross Sectional ◽  
Public Health Center ◽  
Level Of Knowledge

ABSTRAK Indikator D/S di wilayah kerja Puskesmas Saguling Desa Cipangeran pada tahun 2016 menunjukkan masih rendahnya kunjungan balita dalam kegiatan posyandu dengan rata-rata hanya memcapai 41,5%, sedangkan target standar palayanan kota jumlah D/S yaitu 85%. Tujuan penelitian ini adalah untuk mengetahui keteraturan ibu dalam mengunjungi Posyandu dari faktor pengetahuan di Desa Cipangeran Kecamatan Saguling Kabupaten Bandung Barat tahun 2017. Metode penelitian ini menggunakan metode analitik dengan pendekatan cross sectional. Data yang digunakan adalah data primer. Populasi seluruh balita di wilayah kerja Puskesmas Saguling tahun 2016 sebanyak 424 ibu balita, besar sampel yang diambil 81 ibu balita, pengambilan sampel dengan menggunakan Sampel Random Sampling, pengumpulan data dengan hasil kuesioner berisi pertanyaan untuk mendapatkan data yang berkaitan dengan variabel yang diteliti. Hasil penelitian pengetahuan ibu balita didapatkan hampir setengah berada dikategori cukup yaitu 47 ibu balita (58%), namun masih ada ibu balita yang memiliki pengetahuan baik yaitu 18 ibu balita (22%), dan ibu balita yang memiliki pengetahuan kurang yaitu 16 ibu balita (20%). Kesimpulan dari penelitian didapatkan tingkat pengetahuan ibu balita yang tidak teratur dalam mengunjungi Posyandu di Desa Cipangeran Kecamatan Saguling Kabupaten Bandug Barat hampir setengah ibu balita berpengetahuan cukup. ABSTRACT The D / S indicator in the working area of ​​Saguling Public Health Center of Cipangeran Village in 2016 indicates that the low number of toddler visits in posyandu activities reaches an average of 41.5%, while the standard target for city / city is 85%. The purpose of this study is to determine the regularity of mothers in visiting Posyandu from knowledge factor in Cipangeran Village, Saguling District, West Bandung regency in 2017. This research method using analytical method with cross sectional approach. The data used is primary data.The population of all toddlers in the working area of Saguling Publich Health Center in 2016 were 424 mother, the sample size was 81 mother, using Random Sampling , data collection with questionnaires containing questions to obtain data related to the variables studied. The result of the research of the knowledge of the mother of the toddler is almost sufficient, namely 47 mothers (58%),but there are still mother who have good knowledge that is 18 mother of toddler (22%) and mother with less knowledge that is 16 mother of balita (20%). The conclusion of the research is the level of knowledge of irregular mother in visiting Posyandu in Cipangeran Village, Saguling, of West Bandung district, almost half of the toddler are knowledgeable enough.

The Effect of Money Denomination on Prosocial Behavior: Through the Perspective of Metaphorical Cognitive Theory

2021 ◽  
pp. 003329412110070
Author(s):  
Jianfeng Yang ◽  
Tao Xu ◽  
Yanhui Hou ◽  
Emily C. Monczynski ◽  
Xiaochuan Jiang
Keyword(s):  
Prosocial Behavior ◽  
Sample Size ◽  
Alternative Explanation ◽  
Cognitive Theory ◽  
Design Experiment ◽  
Single Factor ◽  
Behavior Study ◽  
Factor Design ◽  
Factorial Design Experiment ◽  
Practical Implications

Based on metaphorical cognitive theory, this research did four experiments to examine whether and how one important feature of money, denomination, could influence prosocial behavior. Study 1 was an experiment with a sample size of 209 undergraduates ( Mage = 18.97) showed that a larger denomination enhanced the probability of participants engaging in prosocial behavior rather than with a smaller denomination. Study 2 collecting data from 269 undergraduates ( Mage = 18.50) further showed that larger denominations condition inspired more prosocial behavior than the control condition; and the small denominations condition produced similar levels of prosocial behavior to the control condition. Study 3 used single factor design with a sample size of 192 undergraduates ( Mage = 20.49) repeated the results of Study 2. Furthermore, Study 3 excluded an important alternative explanation that the value rather than the denomination influenced prosocial behavior. Last, Study 4 applied a factorial design experiment with a sample size of 132 undergraduates ( Mage = 20.92) which demonstrated that generosity mediated the effect of denomination on prosocial behavior; the effect of denomination on prosocial behavior did not depend on money priming methods. Finally, theoretical and practical implications were discussed.

Bayesian approach to discriminant problems for count data with application to multilocus short tandem repeat dataset

2020 ◽  
Vol 19 (2) ◽  
Author(s):  
Koji Tsukuda ◽  
Shuhei Mano ◽  
Toshimichi Yamamoto
Keyword(s):  
Sample Size ◽  
Classification Accuracy ◽  
Tandem Repeats ◽  
Bayes Factor ◽  
Characteristic Curve ◽  
Geometric Mean ◽  
Previous Method ◽  
Threshold Adjustment ◽  
Two Populations ◽  
Short Tandem

AbstractShort Tandem Repeats (STRs) are a type of DNA polymorphism. This study considers discriminant analysis to determine the population of test individuals using an STR database containing the lengths of STRs observed at more than one locus. The discriminant method based on the Bayes factor is discussed and an improved method is proposed. The main issues are to develop a method that is relatively robust to sample size imbalance, identify a procedure to select loci, and treat the parameter in the prior distribution. A previous study achieved a classification accuracy of 0.748 for the g-mean (geometric mean of classification accuracies for two populations) and 0.867 for the AUC (area under the receiver operating characteristic curve). We improve the maximum values for the g-mean to 0.830 and the AUC to 0.935. Computer simulations indicate that the previous method is susceptible to sample size imbalance, whereas the proposed method is more robust while achieving almost identical classification accuracy. Furthermore, the results confirm that threshold adjustment is an effective countermeasure to sample size imbalance.

scholarly journals Willingness of Greek general population to get a COVID-19 vaccine

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Georgia Kourlaba ◽  
Eleni Kourkouni ◽  
Stefania Maistreli ◽  
Christina-Grammatiki Tsopela ◽  
Nafsika-Maria Molocha ◽  
...  
Keyword(s):  
Public Health ◽  
General Population ◽  
Data Collection ◽  
Sample Size ◽  
Significant Proportion ◽  
Control Measures ◽  
Systematic Sampling ◽  
Computer Assisted ◽  
Public Health Officials ◽  
To Receive

Abstract Background Epidemiological data indicate that a large part of population needs to be vaccinated to achieve herd immunity. Hence, it is of high importance for public health officials to know whether people are going to get vaccinated for COVID-19. The objective of the present study was to examine the willingness of adult residents in Greece to receive a COVID-19 vaccine. Methods A cross-sectional was survey conducted among the adult general population of Greece between April 28, 2020 to May 03, 2020 (last week of lockdown), using a mixed methodology for data collection: Computer Assisted Telephone Interviewing (CATI) and Computer Assisted web Interviewing (CAWI). Using a sample size calculator, the target sample size was found to be around 1000 respondents. To ensure a nationally representative sample of the urban/rural population according to the Greek census 2011, a proportionate stratified by region systematic sampling procedure was used to recruit particpants. Data collection was guided through a structured questionnaire. Regarding willingness to COVID-19 vaccination, participants were asked to answer the following question: “If there was a vaccine available for the novel coronavirus, would you do it?” Results Of 1004 respondents only 57.7% stated that they are going to get vaccinated for COVID-19. Respondents aged > 65 years old, those who either themselves or a member of their household belonged to a vulnerable group, those believing that the COVID-19 virus was not developed in laboratories by humans, those believing that coronavirus is far more contagious and lethal compared to the H1N1 virus, and those believing that next waves are coming were statistically significantly more likely to be willing to get a COVID-19 vaccine. Higher knowledge score regarding symptoms, transmission routes and prevention and control measures against COVID-19 was significantly associated with higher willingness of respondents to get vaccinated. Conclusion A significant proportion of individuals in the general population are unwilling to receive a COVID-19 vaccine, stressing the need for public health officials to take immediate awareness-raising measures.

Sign in / Sign up

Export Citation Format

Share Document