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Testing a Claim about Standard Deviation01:19

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A complete procedure to test a claim about population standard deviation or population variance is explained here.
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In practice, we rarely know the population standard deviation. In the past, when the sample size was large, this did not present a problem to statisticians. They used the sample standard deviation s as an estimate for σ and proceeded as before to calculate a confidence interval with close enough results. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
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Effective sample preparation is crucial for accurate and reliable laboratory analysis. During this process, two significant sources of error can arise: concentration bias from improper sample splitting and contamination caused by methods used to reduce particle size, such as grinding or homogenization. Identifying and minimizing these potential errors is crucial to ensuring the validity of the analysis.
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Application of Different Standard Error Estimates in Reliable Change Methods.

Dustin B Hammers1,2, Kevin Duff1,2

  • 1Center for Alzheimer's Care, Imaging, and Research, Department of Neurology, University of Utah, Salt Lake City, UT, USA.

Archives of Clinical Neuropsychology : the Official Journal of the National Academy of Neuropsychologists
|November 17, 2019
PubMed
Summary
This summary is machine-generated.

Standard error (SE) terms are applicable in clinical research for assessing cognitive performance changes. Both SE of the estimate (SEest) and SE for prediction (SEpred) yield comparable results for reliable change statistics.

Keywords:
AssessmentMild cognitive impairmentReliable changeStandard error

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Area of Science:

  • Neuroscience
  • Psychology
  • Clinical Research

Background:

  • Reliable change methodology is crucial for assessing cognitive performance.
  • Short-term practice effects can influence cognitive assessments.
  • Standard error (SE) terms are used to evaluate the reliability of change.

Purpose of the Study:

  • To clarify the applicability of standard error (SE) terms in clinical research.
  • To examine the impact of short-term practice effects on cognitive performance.
  • To compare SE of the estimate (SEest) and SE for prediction (SEpred) in reliable change methodology.

Main Methods:

  • Compared SEest and SEpred using a developmental sample (n=167) with normal cognition or mild cognitive impairment (MCI).
  • Assessed participants twice over one week to capture practice effects.
  • Applied standardized regression-based (SRB) reliable change prediction equations to an independent MCI sample (n=143).

Main Results:

  • SEest and SEpred values were nearly identical in the clinical sample.
  • Resultant SRB-based discrepancy z scores were comparable and strongly correlated (r=1.0, p<.001).
  • Observed follow-up scores for MCI participants were below expectation based on SRB algorithms.

Conclusions:

  • Calculating SEest and SEpred from clinical samples yields similar values for reliable change statistics.
  • Neuropsychologists should consider both mathematical accuracy and ease of use when selecting SE metrics.
  • These findings support the use of SEest and SEpred in SRB reliable change methods for research and clinical practice.