quasi-arithmetical - перевод на Английский
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quasi-arithmetical - перевод на Английский

EMPIRICAL INTERVENTIONAL STUDY USED TO ESTIMATE THE CAUSAL IMPACT OF AN INTERVENTION ON TARGET POPULATION WITHOUT RANDOM ASSIGNMENT
Quasi experiment; Design of quasi-experiments; Quasi-experiments; Quasi experimental design; Quasi-experimental design; Quasi Experiment; Quasi-natural experiment; Quasi-experimental; Quasi-experimental study; Quasi-experimental studies

quasi-arithmetical      
(adj.) = casi aritmético
Ex: Many subjects lend themselves to a quasi-arithmetical arrangement, eg music: solos, duets, trios, etc.
arithmetical      
(n.) = aritmético
Ex: The advanced arithmetical machines of the future will be electrical in nature, and they will perform at 100 times present speeds, or more.
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* quasi-arithmetical = casi aritmético
Arithmetic function         
ANY FUNCTION WHOSE DOMAIN IS THE POSITIVE INTEGERS AND WHOSE RANGE IS A SUBSET OF THE COMPLEX NUMBERS
Arithmetic functions; Arithmetical function; Number-theoretic function; Number-theoretic functions; Number theoretic function; Arithmetical functions; Summatory function
Función aritmética

Определение

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Википедия

Quasi-experiment

A quasi-experiment is an empirical interventional study used to estimate the causal impact of an intervention on target population without random assignment. Quasi-experimental research shares similarities with the traditional experimental design or randomized controlled trial, but it specifically lacks the element of random assignment to treatment or control. Instead, quasi-experimental designs typically allow the researcher to control the assignment to the treatment condition, but using some criterion other than random assignment (e.g., an eligibility cutoff mark).

Quasi-experiments are subject to concerns regarding internal validity, because the treatment and control groups may not be comparable at baseline. In other words, it may not be possible to convincingly demonstrate a causal link between the treatment condition and observed outcomes. This is particularly true if there are confounding variables that cannot be controlled or accounted for.

With random assignment, study participants have the same chance of being assigned to the intervention group or the comparison group. As a result, differences between groups on both observed and unobserved characteristics would be due to chance, rather than to a systematic factor related to treatment (e.g., illness severity). Randomization itself does not guarantee that groups will be equivalent at baseline. Any change in characteristics post-intervention is likely attributable to the intervention.