scholarly journals Hypothesis-Testing Improves the Predicted Reliability of Neuroscience Research

2019 ◽  
Author(s):  
Bradley E. Alger
Keyword(s):  
Hypothesis Testing ◽  
Statistical Tests ◽  
Laboratory Research ◽  
Experimental Sample ◽  
Test Results ◽  
Sample Sizes ◽  
Multiple Tests ◽  
Neuroscience Research ◽  
Statistical Problems ◽  
Adequate Power

AbstractCritics often cite statistical problems as prime contributors to the “reproducibility crisis” of science, expressing great concern about research that bases major conclusions on single p-valued statistical tests. The critics also argue that the predicted reliability of neuroscience research in particular is low because much of the work depends heavily on small experimental sample sizes and, hence, its statistical tests lack adequate “power.”It isn’t known how common the practice of basing major conclusions on single tests is in neuroscience or how the statistical criticisms affect the validity of conclusions drawn by laboratory research that evaluates hypotheses via multiple tests. I review a sample of neuroscience publications to estimate the prevalence and extensiveness of hypothesis-testing research. I then apply R.A. Fisher’s method for combining test results to show that the practice of testing multiple predictions of hypotheses increases the predicted reliability of neuroscience research.

scholarly journals The nuts and bolts of hypothesis testing

2015 ◽  
Vol 3 (3) ◽  
pp. 139-144 ◽  
Author(s):  
Stephanie L. Pugh ◽  
Annette Molinaro
Keyword(s):  
Hypothesis Testing ◽  
Hypothesis Test ◽  
Statistical Tests ◽  
Epidemiological Studies ◽  
Statistical Test ◽  
P Value ◽  
P Values ◽  
Multiple Tests ◽  
Alternative Hypotheses ◽  
Decision Making Tool

Abstract When reading an article published in a medical journal, statistical tests are mentioned and the results are often supported by a P value. What are these tests? What is a P value and what is its meaning? P values are used to interpret the result of a statistical test. Both are intrinsic parts of hypothesis testing, which is a decision-making tool based on probability. Most medical and epidemiological studies are designed using a hypothesis test so understanding the key principles of a hypothesis test are crucial to interpreting results of a study. From null and alternative hypotheses to the issue of multiple tests, this paper introduces concepts related to hypothesis testing that are crucial to its implementation and interpretation.

scholarly journals Routes to Research for Novice Undergraduate Neuroscientists

2006 ◽  
Vol 5 (2) ◽  
pp. 175-187 ◽  
Author(s):  
Kyle J. Frantz ◽  
Robert L. DeHaan ◽  
Melissa K. Demetrikopoulos ◽  
Laura L. Carruth
Keyword(s):  
Undergraduate Students ◽  
Attitudes Toward Science ◽  
Laboratory Research ◽  
Research Experience ◽  
Neuroscience Research ◽  
Long Term Follow Up ◽  
Apprenticeship Model ◽  
Design Experiments

Undergraduate students may be attracted to science and retained in science by engaging in laboratory research. Experience as an apprentice in a scientist's laboratory can be effective in this regard, but the pool of willing scientists is sometimes limited and sustained contact between students and faculty is sometimes minimal. We report outcomes from two different models of a summer neuroscience research program: an Apprenticeship Model (AM) in which individual students joined established research laboratories, and a Collaborative Learning Model (CLM) in which teams of students worked through a guided curriculum and then conducted independent experimentation. Assessed outcomes included attitudes toward science, attitudes toward neuroscience, confidence with neuroscience concepts, and confidence with science skills, measured via pre-, mid-, and postprogram surveys. Both models elevated attitudes toward neuroscience, confidence with neuroscience concepts, and confidence with science skills, but neither model altered attitudes toward science. Consistent with the CLM design emphasizing independent experimentation, only CLM participants reported elevated ability to design experiments. The present data comprise the first of five yearly analyses on this cohort of participants; long-term follow-up will determine whether the two program models are equally effective routes to research or other science-related careers for novice undergraduate neuroscientists.

scholarly journals Is preregistration worthwhile?

2019 ◽  
Author(s):  
Aba Szollosi ◽  
David Kellen ◽  
Danielle Navarro ◽  
Rich Shiffrin ◽  
Iris van Rooij ◽  
...  
Keyword(s):  
Statistical Models ◽  
Statistical Tests ◽  
Error Rates ◽  
Statistical Techniques ◽  
Weak Version ◽  
Strong Version ◽  
Statistical Problems

Proponents of preregistration argue that, among other benefits, it improves the diagnosticity of statistical tests [1]. In the strong version of this argument, preregistration does this by solving statistical problems, such as family-wise error rates. In the weak version, it nudges people to think more deeply about their theories, methods, and analyses. We argue against both: the diagnosticity of statistical tests depend entirely on how well statistical models map onto underlying theories, and so improving statistical techniques does little to improve theories when the mapping is weak. There is also little reason to expect that preregistration will spontaneously help researchers to develop better theories (and, hence, better methods and analyses).

scholarly journals Pengaruh Harga, Kualitas Pelayanan, dan Costumer Relationship Management Terhadap Keputusan Pembelian Pada Asuransi Astra (Garda OTO)

2021 ◽  
Vol 4 (2) ◽  
pp. 673-679
Author(s):  
Dhita Adriani Rangkuti ◽  
Mey Monita Lestari Manalu ◽  
Sartika Nanda Lestari ◽  
Brian Robuli ◽  
Irfan Boy Samosir
Keyword(s):  
Service Quality ◽  
Hypothesis Testing ◽  
Customer Relationship Management ◽  
Significant Influence ◽  
Relationship Management ◽  
Customer Relationship ◽  
Primary Data ◽  
Test Results ◽  
Purchasing Decisions ◽  
F Test

The purpose of this study was to determine and analyze the effect oprice, service quality, and customer relationship management on the purchase decision of Asuransi Astra Garda OtoMedan, JL.ImanBonjol. The data used are primary data obtained from the answer of 85 respondents by accidental sampling method. Data collection techniques used in this study used a questionnaire and interview technique. Data analysis techniquesin the study used linear regression, classic assumption  tests, hypothesis testing (t test and f test) and the coefficiecnt of determination. Hypothesis testing results indicate that partially (t) obtained value for t count price of 2,833 > t table 1,658 and sig value obtained 0,005<0,05 which means that price has a positive and significant influence on purchasing decisions in using Astra Insurance services (Garda Oto). Partially obtained value for service quality tcount 5.152 >ttable 1.658 and sig value obtained 0.000 <0.05 which means that service quality has a positive and significant influence on purchasing decisions in using Astra Insurance (Garda Oto) services, partially obtained value for customer relationship management t count 8.878 > 1.658 t table and the sig value obtained is 0.000 <0.05 which means that customer relationship management has a positive and significant influence on purchasing decisions in using Astra Insurance (Garda Oto) services, for the F test results obtained calculated F value = 77.769 > f table (2.69), and a significance probability of 0.000 <0.05, meaning that simultaneously prices, service quality and customer relationship management have a positive and significant effect on purchasing decisions in using Astra Insurance Services (Garda Oto). Keywords: Price, Service Quality, and Customer Relationship Management.

scholarly journals ANALISIS PERBANDINGAN GOOD CORPORATE GOVERNANCE BAZNAS DAN LAZNAS

2019 ◽  
Vol 9 (2) ◽  
pp. 97-110
Author(s):  
Sri Wahjuni Latifah ◽  
Siska Aprilia ◽  
Dhaniel Syam
Keyword(s):  
Corporate Governance ◽  
Content Analysis ◽  
Hypothesis Testing ◽  
Annual Report ◽  
Test Results ◽  
Good Corporate Governance ◽  
Analysis Technique

Abstrak Penelitian ini bertujuan untuk menganalisis perbandingan Good Corporate Governance ( Badan Amil Zakat nasional)  dan Laznas(Lembaga Amil Zakat Nasiona. Sampel penelitian ini sebanyak delapan belas(18) Baznas dan Laznas di Jawa Timur. Jenis dan sumber data diperoleh dari laporan tahunan badan atau lembaga amil zakat nasional di Jawa Timur tahun 2016-2017 yang diterbitkan di website resmi pid.baznas.go.id. Data dianalisis dengan beberapa tahap, yaitu melakukan content analysis dan  dilakukan uji hipotesis dengan Mann Whitney U Test. Hasil penelitian menunjukkan  uji Mann Whitney U Test sebesar 0.003,  dengan demikian terdapat perbedaan yang signifikan terhadap penerapan GCG Baznas dengan Laznas. Baznas lebih baik dalam menerapkan good corporate governance dibandingkan pada Laznas.Kata Kunci: Baznas, Laznas, Good Corporate Governance.AbstractThis study aims to compare the good corporate governance of the Baznas(Amil Zakat Agency) and Laznas(the National Amil Zakat Institution). The samples used in this study were 18 Amil Zakat Bodies and Amil Zakat Institutions. The types and sources of data are obtained from the annual report of the national amil zakat agency or institution in East Java for 2016-2017 which is published  on the official website of pid.baznas.go.id. The analysis technique in this study was to conduct content analysis, then carried out hypothesis testing with the Mann Whitney U Test. The Mann Whitney U Test results of 0.003 , which means there are significant differences. Based on the results of the study, the authors can conclude that there are differences in the application of good corporate governance at the Baznas with Laznas. The Baznas is better at implementing good corporate governance than at the Laznas.Keywords: Baznas, Laznas, Good Corporate Governance.

scholarly journals The Effect Of Counseling On The Adherence Of Therapeutic Hypertension Patients

2020 ◽  
Vol 11 (2) ◽  
Author(s):  
Gita Sekar Prihanti ◽  
Novi Puspita Sari ◽  
Nur Indah Septiani ◽  
Laura Putri Risty L. Tobing ◽  
Annisa Rahayu Adrian ◽  
...  
Keyword(s):  
Family Support ◽  
Statistical Tests ◽  
Adherence Rate ◽  
Test Results ◽  
A Value ◽  
Significant Difference ◽  
Post Test ◽  
Lifestyle Education ◽  
Nonparametric Statistical ◽  
Adherence To Therapy

Failure of therapy is a result of bad adherence  medication. Non-adherence to therapy is a major factor that is suspected to result in uncontrolled blood pressure in hypertensive patients resulting in more serious complications. Therefore it is important to increase the adherence rate of treatment in patients with hypertension in the treatment process. For this reason, the need for interventions to improve  adherence  with several aspects that can be changed. This study uses One Group Pretest-Posttest Design using 100 samples. Data derived from questionnaires containing 25 items of adherence to therapy, 5 items of knowledge, 4 items of trust, 3 items of motivation, 10 items of family support with nonparametric statistical tests used were Mc Nemar test. Mc Nemar test results indicate that there is a significant difference between adherence at the pre-test and at the post-test after counseling with a significance value (p = 0,000). The results also showed that there was a difference in knowledge with a significance value (p = 0.001), motivation with a value (p = 0.031) and family support with a value (p = 0,000). The education with counseling about knowledge, trust, motivation and family support is effective in increasing compliance. There are other changeable factors such as lifestyle education, patient doctor relationships, and the use of smartphone applications for self-reported therapy can improve adherence in patients thereby minimizing therapy failure. Other educational methods that can be used besides counseling are counseling and dissemination of social media information.

scholarly journals Some Nonparametric Statistical Tests for Quick Evaluation of Clinical Data

1975 ◽  
Vol 21 (3) ◽  
pp. 309-314 ◽  
Author(s):  
E Melvin Gindler
Keyword(s):  
Control Chart ◽  
Patient Population ◽  
Statistical Tests ◽  
Test Results ◽  
Laboratory Error ◽  
Unusual Distribution ◽  
Run Test ◽  
Nonparametric Statistical ◽  
And Control ◽  
The Given

Abstract Some rapid statistical tests give (a) rapid answers on how well methods agree and control chart evaluation (sign and run tests) and (b) evaluation of distribution of test results (Tukey's quick test and run test). These tests mainly require counting of data and the use of the given nomograms. An unusual distribution of patient test values—that is, unusual when compared with the generally observed distribution of the data seen in a particular laboratory—may indicate laboratory error, alteration of specimens (as from poor collection and/or storage techniques, such as evaporation), or an unusual patient population.

scholarly journals An Evaluation of Four Solutions to the Forking Paths Problem: Adjusted Alpha, Preregistration, Sensitivity Analyses, and Abandoning the Neyman-Pearson Approach

2017 ◽  
Vol 21 (4) ◽  
pp. 321-329 ◽  
Author(s):  
Mark Rubin
Keyword(s):  
Hypothesis Testing ◽  
Present Article ◽  
Type I Error ◽  
Statistical Analyses ◽  
Nonlinear Transformation ◽  
Sensitivity Analyses ◽  
Type I ◽  
Alternative Analysis ◽  
Multiple Tests ◽  
Alpha Level

Gelman and Loken (2013 , 2014 ) proposed that when researchers base their statistical analyses on the idiosyncratic characteristics of a specific sample (e.g., a nonlinear transformation of a variable because it is skewed), they open up alternative analysis paths in potential replications of their study that are based on different samples (i.e., no transformation of the variable because it is not skewed). These alternative analysis paths count as additional (multiple) tests and, consequently, they increase the probability of making a Type I error during hypothesis testing. The present article considers this forking paths problem and evaluates four potential solutions that might be used in psychology and other fields: (a) adjusting the prespecified alpha level, (b) preregistration, (c) sensitivity analyses, and (d) abandoning the Neyman-Pearson approach. It is concluded that although preregistration and sensitivity analyses are effective solutions to p-hacking, they are ineffective against result-neutral forking paths, such as those caused by transforming data. Conversely, although adjusting the alpha level cannot address p-hacking, it can be effective for result-neutral forking paths. Finally, abandoning the Neyman-Pearson approach represents a further solution to the forking paths problem.

Use of Ten Gram Samples of Corn for Determination of Mycotoxins

1988 ◽  
Vol 71 (1) ◽  
pp. 41-43
Author(s):  
Octave J Francis ◽  
George M Ware ◽  
Allen S Carman ◽  
Gary P Kirschenheuter ◽  
Shia S Kuan
Keyword(s):  
Statistical Tests ◽  
Automated System ◽  
Sample Sizes ◽  
Concentration Variance ◽  
Assay Procedure ◽  
Coefficients Of Variation ◽  
The Mean ◽  
Aflatoxin B ◽  
Test Result

Abstract Data were gathered, during a study on the development of an automated system for the extraction, cleanup, and quantitation of mycotoxins in corn, to determine if it was scientifically sound to reduce the analytical sample size. Five, 10, and 25 g test portions were analyzed and statistically compared with 50 g test portions of the same composites for aflatoxin concentration variance. Statistical tests used to determine whether the 10 and 50 g sample sizes differed significantly showed a satisfactory observed variance ratio (Fobs) of 2.03 for computations of pooled standard deviations; paired f-test values of 0.952, 1.43, and 0.224 were computed for each of the 3 study samples. The results meet acceptable limits, since each sample’s r-test result is less than the published value of the |t|, which is 1.6909 for the test conditions. The null hypothesis is retained since the sample sizes do not give significantly different values for the mean analyte concentration. The percent coefficients of variation (CVs) for all samples tested were within the expected range. In addition, the variance due to sample mixing was evaluated using radioisotopelabeled materials, yielding an acceptable CV of 22.2%. The variance due to the assay procedure was also evaluated and showed an aflatoxin B, recovery of 78.9% and a CV of 11.4%. Results support the original premise that a sufficiently ground and blended sample would produce an analyte variance for a 10 g sample that was statistically comparable with that for a 50 g sample.

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