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Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
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Simple harmonic motion is the name given to oscillatory motion for a system where the net force can be described by Hooke's law. If the net force can be described by Hooke's law and there is no damping (by friction or other non-conservative forces), then a simple harmonic oscillator will oscillate with equal displacement on either side of the equilibrium position. To derive an equation for period and frequency, the equation of motion is used. The period of a simple harmonic oscillator is given...
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Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation
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An Algorithm for Creating Virtual Controls Using Integrated and Harmonized Longitudinal Data.

William B Hansen1, Shyh-Huei Chen2, Santiago Saldana2

  • 11 Prevention Strategies, Greensboro, NC, USA.

Evaluation & the Health Professions
|May 5, 2018
PubMed
Summary
This summary is machine-generated.

Researchers developed a novel algorithm to create virtual control groups for studies where live controls are scarce. This method uses historical data to generate computer-simulated comparators, aiding in prevention research.

Keywords:
adolescentsalcoholcigarettescontrol groupsharmonizationintegrated data analysismarijuanamissing data imputationpsychosocial mediators

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Area of Science:

  • * Computational Social Science
  • * Public Health Research Methods
  • * Adolescent Substance Use Prevention

Background:

  • * Recruiting live control groups can be challenging in prevention research, especially when programs are widely disseminated.
  • * Randomization is often not feasible in such real-world scenarios, necessitating alternative comparison strategies.
  • * Archived longitudinal data offers a potential resource for developing novel research methodologies.

Purpose of the Study:

  • * To introduce and evaluate a strategy for generating virtual control groups using computer algorithms.
  • * To assess the feasibility of using aggregated virtual cases as experimental comparators.
  • * To address limitations in recruiting live controls for adolescent-focused prevention trials.

Main Methods:

  • * Integrated and harmonized data from eight longitudinal adolescent studies (1980-2010) assessing psychosocial variables and substance use.
  • * Developed an algorithm using percentile scores to create age- and gender-specific latent psychosocial scores for virtual cases.
  • * Validated the algorithm using treatment and control group data from two randomized controlled trials (RCTs).

Main Results:

  • * The algorithm successfully matched pretest prevalence rates between virtual and treatment control groups in both RCTs.
  • * Virtual controls eliminated differential attrition as a threat to validity by matching treatment case occurrence.
  • * Observed increases in substance use prevalence over time, though discrepancies between live and virtual control outcomes were noted.

Conclusions:

  • * The study presents an initial framework for creating virtual controls using a step-by-step algorithmic procedure.
  • * This method offers a viable approach for generating comparators when live controls are difficult to recruit.
  • * Further validation using diverse prevention trial data is recommended to refine the virtual control strategy.