Samenvatting over correlationeel en experimenteel onderzoek grotendeels gebaseerd op het boek Research Methods, ook andere artikelen komen aanbod behorende bij de cursus Basis van Onderzoeksmethoden en Statistiek.
Alle hoofdstukken die behandeld worden in de cursus basis van onderzoeksmethoden en statistiek
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basis van onderzoek en statistiek bos samenvatting research methods artikelen behorende bij bos universiteit van utrecht correlationeel amp experimenteel geüpload op 8 november 2021
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Samenvatting Research Methods in Psychology – Evaluating a World of Information, ISBN: 9780393445213 Kennismaking Met Onderzoeksmethoden En Statistiek (201800022)
Lecture notes Statistical Methods Research Methods in Psychology – Evaluating a World of Information, ISBN: 9780393445213
Samenvatting Methodologie 1, English, jaar 1, periode 1
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Basis van Onderzoek en Statistiek (BOS):
- Samenvatting Research Methods + artikelen behorende bij BOS
- Universiteit van Utrecht
- Correlationeel & experimenteel
- Geüpload op 8 november 2021
Week 1 Correlationeel
- Research Methods:
o Three Claims, Four Validities: p. 57 t/m 85
o Identifying Good Measurement: p.117 t/m 128, p. 132
t/m 149
- Research Methods:
o Surveys and Observations: p. 153 t/m 177 o Survey Research: 193-200, 202 t/m 233
Aantekeningen Correlationeel onderzoek:
o Three Claims, Four Validities: p. 57 t/m 85
The three types of claims – frequency claims, association claims and causal claims – make
statements about variables or about relationships between variables.
A variable, as the word implies, is something that varies, so it must have at least two levels,
or values smoker or non-smoker.
Constant is something that could potentially vary but that has only one level in the study in
question.
Measured variable; is one whose levels are simply observed and recorded. Measuring a
variable is a matter of recording an observation, a statement, or a value as it occurs
naturally.
Manipulated variable; is a variable a researcher controls, usually by assigning study
participant to the different levels of that variable one respondent gets 10 mg, the other
20 mg.
Some variables cannot be manipulated – they can only be measured age, IQ
Conceptual variables (construct); are abstract concepts, such as ‘spending time socializing’
and school achievements.
Conceptual variables must be carefully defined at the theoretical level, and these definitions
are called conceptual definitions.
When testing hypothesis with empirical research, operational definitions of variables are
created, also known as operational variables, or operationalizations. To operationalize
,means to turn a concept of interest into a measured or manipulated variable (page 60
Table).
A claim is an argument someone is trying to make (page 62 Table 3.2).
Frequency claims: describe a particular rate or degree of a single variable measured
Association claim: two variables go together; one level of a variable is likely to be associated
with a particular level of another variable. Correlate or covary; when one variable changes,
the other variable changes as well. They are related
correlational study (when two variables are measured)
Positive, negative, and zero association
Positive association/correlation; high goes with high, and low goes with low. positive
slope
Scatterplot: one way to represent an association (Read page 65).
Negative association/correlation or inverse association; high goes with low and low goes
with high negative slope
Zero association/correlation; no association between the variables horizontal line
Both positive and negative associations can help us make predictions, but zero associations
cannot. With a zero correlation, we cannot predict the level of one variable from the level of
the other.
Association claims use verbs as link, associate, correlate, predict, tie to, being at risk for, is
related to, and linked to.
Causal claim: music lessons enhance IQ
Whereas an association claim merely notes a relationship between two variables, a causal
claim goes even further, arguing that one of the variables is responsible for changing the
other.
Causal claims, go beyond a simple association between two variables. They use language
suggesting that one variable causes the other – verbs such as cause, enhance, affect and
change, reduces, leads to.
Or tentative language – could, may, seem, suggest, sometimes, potentially.
Advice also if you do X, Y will happen (page 67 Table 3).
Three criteria for causal claims
1. Two variables (the causal variable and the outcome variable) are correlated; the
relationship cannot be zero.
2. It must show that the causal variable came first, and the outcome variable came later
, 3. It must establish that no other explanations exist for the relationship.
only one type of study, an experiment, can enable researchers to support a causal claim
because it meets all three criteria.
Validity refers to the appropriateness of conclusion or decision, and in general, a valid claim
is reasonable, accurate, and justifiable.
Interrogating frequency claims
- To evaluate how well a study supports a frequency claim, you will focus on two of
their validities, construct and external validity. Sometimes statistical validity, too
Construct validity refers to how well a conceptual variable is operationalized.
how well a study measured or manipulated a variable.
variables need to be measured reliably (meaning the measure yields similar scores on
repeated testing) and that different levels of a variable accurately correspond to true
differences in, say, depression or happiness.
External validity of frequency claims
Generalizability: how did the researchers choose the study’s participants, and how well do
those participants represent the intended population?
External validity: how well the results of the study generalize to, or represent, people or
contexts besides those in the original study.
Statical validity/statistical conclusion validity; is the extent to which a study’s statistical
conclusions are accurate and reasonable. How well do the numbers support the claim?
The percentage reported in a frequency claim is usually accompanied by a margin of error of
the estimate; this is a statistical figure, based on sample size for the study, that attempts to
include the true value in the population. It helps us describe how well our sample estimates
the true percentage.
Interrogating association claims
To interrogate an association claim, you ask how well the correlational study behind the
claim supports construct, external, and statistical validities.
Association claim two variables measure each variable
External validity of association claims you can evaluate generalizability
Statistical validity strength; how strong is the association? (page 72 Table 3.4)
, Common mistakes statistical validity.
- False positive/type 1 error; a study mistakenly concludes, based on the results from a
sample of people, that there is association between two variables, when there really
is no association in the full population.
- Type 2 error: a study might mistakenly conclude from a sample that there is no
association between two variables, when there really is an association in the full
population.
Summery
When you come across an association claim, you should ask about three validities:
- Construct, external, and statistical.
- You can ask how well the two variables were measured (construct validity).
- You can ask whether you can generalize the result to a population (external validity)
You can evaluate the strength and significance of the association (statistical validity) (page
73 Table 3,5).
Interrogating causal claim.
Three criteria for causation:
- Covariance
- Temporal precedence
- Internal validity
Covariance: the extent to which two variables are observed to go together, is determined by
the results of a study.
Temporal precedence: one variable comes first in time, before the other variable.
Internal validity or third variable criterion; is an indication of a study’s ability to eliminate
alternative explanations for the association (page 74 Table 3,6)
to support a causal claim, researchers must conduct a well-designed experiment, in which
one variable is manipulated and the other is measured.
researchers manipulate the variable they think is the cause and measure the variable they
think is the effect (or outcome).
In the context of an experiment the manipulated variable is called the independent variable
and the measured variable is called the dependent variable.
To manipulate a variable means to assign participant to be at one level or the other.
A study’s method can establish temporal precedence and internal validity.
Random assignment: ensure that the children in all the groups were as similar as possible.
Random assignment increases internal validity.
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