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Related Concept Videos

Types of Hypothesis Testing01:11

Types of Hypothesis Testing

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There are three types of hypothesis tests: right-tailed, left-tailed, and two-tailed.
When the null and alternative hypotheses are stated, it is observed that the null hypothesis is a neutral statement against which the alternative hypothesis is tested. The alternative hypothesis is a claim that instead has a certain direction. If the null hypothesis claims that p = 0.5, the alternative hypothesis would be an opposing statement to this and can be put either p > 0.5, p < 0.5, or p...
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Statistical Hypothesis Testing01:16

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Hypothesis testing is a critical statistical procedure facilitating informed, evidence-based decisions. It begins with a hypothesis, which is a tentative explanation, or a prediction about a population parameter. This hypothesis can be either a null hypothesis (H0), indicating no effect or difference, or an alternative hypothesis (Ha), suggesting an effect or difference.
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Accuracy and Errors in Hypothesis Testing01:13

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Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
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Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data01:16

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Statistical inference techniques, paramount in hypothesis testing, differentiate into two broad categories: parametric and nonparametric statistics.
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
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What is a Hypothesis?01:14

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A hypothesis can be a simple sentence or statement about a property or any phenomenon observed or predicted for a population. It is usually a claim about a  property of the population. It can be stated for any field observations or experiments. A hypothesis statement cannot be said to be right or wrong as it is merely a statement. It needs to be tested through an elaborate data collection process and an appropriate statistical test. A hypothesis should be a general but not a vague...
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A hypothesis testing procedure for random changepoint mixed models.

Corentin Segalas1, Hélène Amieva1, Hélène Jacqmin-Gadda1

  • 1INSERM, Bordeaux Population Health Research Center, University of Bordeaux, Bordeaux, France.

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Summary

This study introduces a new statistical method to detect accelerated cognitive decline before Alzheimer's disease diagnosis. The method confirms that educational level influences cognitive reserve and the rate of decline.

Keywords:
Alzheimercognitive reservenonidentifiabilityrandom changepointscore test

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Area of Science:

  • Biostatistics
  • Neuroscience
  • Gerontology

Background:

  • Alzheimer's disease diagnosis often occurs after significant cognitive decline.
  • Individual characteristics influence the trajectory of cognitive decline.
  • Identifying prediagnosis decline is crucial for understanding disease progression.

Purpose of the Study:

  • To develop statistical methods for detecting a random changepoint indicating accelerated cognitive decline.
  • To assess the existence of a prediagnosis phase of accelerated decline in Alzheimer's disease.

Main Methods:

  • Utilized a mixed-effects model with two linear phases to analyze biomarker trajectories.
  • Employed a supremum score test statistic to address nuisance parameter issues under the null hypothesis.
  • Applied multiplier bootstrap for approximating the asymptotic distribution of the test statistic.

Main Results:

  • The proposed testing procedure demonstrated good performance in simulations.
  • The statistical test was applied to the PAQUID cohort, analyzing prediagnosis cognitive decline.
  • The analysis revealed significant prediagnosis decline for all educational levels studied.

Conclusions:

  • The developed inferential methods effectively detect accelerated cognitive decline phases.
  • Educational level serves as a significant indicator of cognitive reserve.
  • Higher educational attainment is associated with better cognitive reserve, potentially delaying or mitigating decline.