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Related Concept Videos

Types of Selection01:46

Types of Selection

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Natural selection influences the frequencies of particular alleles and phenotypes within populations in several different ways. Primarily, natural selection can be directional, stabilizing, or disruptive. Directional selection favors one extreme trait and shifts the population towards that phenotype while selecting against individuals displaying alternate traits. Stabilizing selection favors an intermediate trait with a narrow range of variation. Deviation from the optimal phenotype towards an...
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The mode is one of the commonly used measures of a central tendency. It is defined as the most frequent value in a data set.
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Frequency-dependent Selection01:21

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When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
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The measures of central tendency calculated from a data set may not reveal much about its intrinsic distribution. If a plot is made of the data set’s values, the mean and the median may not only differ, but also the plot may have more values on one side of the central tendencies. Such a data set is said to be skewed towards that side.
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Mate Choice01:20

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Mate choice—the decision about whom to mate with—is a type of natural selection, since animals must reproduce to pass down their genes. Mate choice is also called intersexual selection because the behavior occurs between the sexes.
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Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
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Disentangling Selection Into Mode From Mode Effects.

Colm O'Muircheartaigh1, L Philip Schumm2, Ned English3

  • 1Harris School of Public Policy, University of Chicago, Chicago, Illinois, USA.

The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences
|August 20, 2024
PubMed
Summary
This summary is machine-generated.

Data collection mode had minimal impact on health reporting in the National Social Life, Health, and Aging Project (NSHAP). However, comparing all respondents by mode produced misleading results, highlighting the need for careful analysis of data collection methods.

Keywords:
Experimental designMode effectsMultimodeSurveys

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Area of Science:

  • Gerontology
  • Survey Methodology
  • Sociology

Background:

  • The National Social Life, Health, and Aging Project (NSHAP) collects crucial data on aging.
  • Data collection modes can influence survey responses.
  • Understanding these influences is vital for accurate research.

Purpose of the Study:

  • To assess the impact of remote versus in-person data collection on NSHAP Round 4 responses.
  • To guide appropriate methods for addressing mode differences in analyses.

Main Methods:

  • A randomized experiment compared remote and in-person interviews for a subset of NSHAP respondents.
  • Response rates and key outcomes were compared between experimental groups.
  • All Round 4 respondents were analyzed based on their final data collection mode.

Main Results:

  • No significant differences in physical/mental health or simple recall were found between remote and in-person modes in the randomized experiment.
  • In-person interviews showed slightly lower cognitive function scores on specific tasks.
  • Remote respondents reported fewer social network members.
  • Comparing all respondents by final mode yielded substantially different, potentially misleading, results.

Conclusions:

  • Data collection mode did not significantly affect self-reported health in NSHAP.
  • Mode moderately impacted other variables, such as social network size and certain cognitive measures.
  • Naive comparisons of all respondents by mode are inappropriate for adjusting data and can yield misleading findings.