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Research in Biomedical Sciences (AB_1142): Complete Summary (VU Amsterdam)

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The summary is written in alignment with the course material (the book and the lectures), and it contains all the content necessary to pass the exam.

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Subido en
22 de diciembre de 2022
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133
Escrito en
2021/2022
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Lecture 1 – Recap




1. Methodology


Variables

− observable or hypothetical events that can change and whose changes can be measured in
some way
− independent variables – explanatory variables
− manipulated variable controlled by experimenter
− predictor
− dependent variables – response variables
− observed effect
− outcome

,− extraneous variables
− variables that are not of interest to the researcher but that might influence the
variables of interest if not controlled
− variables that provide alternative explanation
− if not controlled -> confounding variable


Variables: levels of measurement

− nominal – variable represents a category without logical order
− if there’s only 2 categories – dichotomous
− e.g., What is your sex? (female vs. male)
− e.g., What is your favorite color? (red vs. blue vs. ...)
− e.g., What type of respiratory disease do you have? (Asthma vs. COPD vs.
emphysema vs. ...)
− ordinal – ranked variable, represents a category with a specific order or rank position
− e.g., What is your position in the race? (1st, 2nd, last...)
− e.g., What is your position in height ranking? (tallest, shortest,..)
− e.g., How good is your lung function? (horrible, bad, reasonable, good, excellent)
− discrete – counts, finite values
− e.g., How many times does the rat push the lever?
− e.g., How many times per week do you go to the grocery store?
− e.g., How many times do you cough?
− continuous – scale variable with infinite values
− e.g., How much does this package weigh?
− e.g., What is the distance between you and the blackboard?
− e.g., What is your lung volume in liters?

,Research design

− research question
− causal effect or association
− dependent variables
− measurement
− type (nominal, ordinal, discrete, continuous)
− number of variables
− independent variables
− measurement
− type (nominal, ordinal, discrete, continuous)
− number of variables
− manipulation
− compare groups or conditions, the number of
− Are measurements/manipulations dependent/within-subjects/paired or
independent/between-subjects/not paired?

, − cross-sectional design – a type of research design in which you collect data from many
different individuals at a single point in time
− in cross-sectional research, the variables are observed without influencing them
− case control design – a study that compares patients who have a disease or outcome of
interest (cases) with patients who do not have the disease or outcome (controls), and looks
back retrospectively to compare how frequently the exposure to a risk factor is present in
each group to determine the relationship between the risk factor and the disease
− no intervention is attempted, and no attempt is made to alter the course of the
disease
− cohort design – a type of research design that follow groups of people over time
− a particular form of longitudinal study that samples a cohort, performing a cross-
section at intervals through time
− randomized control design – a study design that randomly assigns participants into an
experimental group or a control group
− as the study is conducted, the only expected difference between the control and
experimental groups in a randomized controlled trial (RCT) is the outcome variable
being studied
− cross-over design – a longitudinal study in which subjects receive a sequence of different
treatments
− 2 or more interventions are assessed
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Slaying Biomedical Sciences

I study the Bachelor Biomedical Sciences at the Vrije Universiteit Amsterdam (VU) and I regularly write extensive notes, which later on can be used as complete study material. The summaries include all the information relevant (and more) from both the books and the lectures provided by the professors. I am a perfectionist so I always do my best to make my summaries as comprehensible (and pretty) as possible!

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