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Research Methods > Chapter 3 Three Claims, Four Validities: Interrogation Tools For Consumers Of Research > Flashcards

Chapter 3 Three Claims, Four Validities: Interrogation Tools For Consumers Of Research Flashcards

1
Q

What are the three claims??

A
  1. frequency
  2. association
  3. causal
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2
Q

What do claims do?

A
  • make a statement about variable or about relationships between variables
  • argument someone is trying to make
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3
Q

What is a variable?

A
  • something that varies, it must have at least two levels (values)
  • *core unit of psychological research (DV)
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4
Q

What is a constant variable?

A
  • something that could potentially vary but that has only one level in the study in question (IV)
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5
Q

What is a manipulated variable?

A
  • we control its levels by assigning participants to the varying levels of the variable
    ex: P1 gets 20mg, P2 40mg etc
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6
Q

Measured variable?

A
  • researchers record an observation, statement or value
    ex: IQ, BP, Height
    also abstract variables like depression
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7
Q

Variables can be described in what two ways?

A
  1. Conceptual definition

2. Operational definition

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8
Q

What is a conceptual definition of a variable?

A
  • when researchers discuss theory or journalists write about research….(abstract concepts)
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9
Q

What is an operational definition of a variable?

A
  • when one turns a concept of interest not a measured or manipulated variable….needed for testing hypotheses via empirical research
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10
Q

Give a run through example of both variable definitions.

A
  1. conceptual definition: weight gain

2. operational definition: WEIGH THEM

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11
Q

How are variables commonly stated as definition wise?

A
  • conceptually
  • to find out the operationalized variable look at how they were measured!
    ex How did they measure “X”.
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12
Q

Describe what a frequency claim is!

A
  • describe a rate or level of something
    ex: More than 2 million US teens Depressed
  • two million= frequency/count
  • they claim how frequent something is
  • claims that mention the % of a variable…the # of people who fit the description or some group lvl
  • do not show an associating between them and it does not claim one caused the other
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13
Q

Frequency Claims only focus on how many variables? Measured or Manipulated?

A
  • only one variable

- ONLY MEASURED

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14
Q

Are Anecdotal claims frequency claims?

A

NO

  • they report a problem but do not say anything about the frequency or rate….
  • no report of the results of a social science study…they just show an illustrative story (no empirical back up)
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15
Q

What is an Association claim?

**also word indicators??*

A
  • argues that one level of a variable is LIKELY to be ASSOCIATED with a particular lvl of another variable
  • also called a correlate
  • linked, association, correlated, pedicured, tied to, is at risk for
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16
Q

Association claims involve how many variables?Measured , manipulated?

A 
at least two
only MEASURED  (this is what separates it from causal claims)
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17
Q

What are used to see if two variables are related after measuring variables for an association claim?

A
  • descriptive statistics
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18
Q

What are the four types of Association Claims?

A
  1. positive associations
  2. negative associations
  3. zero associations
  4. curvilinear associations
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19
Q

Explain what a Positive Association is!

  • also called?
  • ex?
  • reped by?
A
  • aka + correlation
  • high scores go with high scores; low scores go with low scores
    Ex: High scores of abnormal fat go with more dementia symptoms
    Ex: Low scores of abnormal fat go with less dementia symptoms
  • scatterplots
20
Q

Explain what a Negative Association is!

  • also called?
  • ex?
  • reped by?
  • what does the negative refer to?
A
  • aka - correlation or inverse association
  • high scores go with low scores, and low scores go with high scores.
  • ex: High rates of cell phone usage tied to low sperm quality
  • scatterplot
  • negative only refers to the slope it does not mean the relationship is bad!
21
Q

Explain Zero association claims!

  • ex?
  • reped by?
A
  • no association btwn the variables
  • cloud of spots that has no slope and therefore a line draw through it would be nearly horizontal which has a slope of zero.
    Ex: ADHD is NOT linked to future drug abuse
  • scatterplot
22
Q

Explain Curvilinear Association claims!

  • ex
  • reped by
A
  • the level of one variable changes its pattern as the other variable increases.
    -ex: Relationships btwn Age and frequency of health care visits
    ( its a u relationship……when your young you visit a lot…as you get older not so much…then it increases once you are elderly)
  • scatterplot
23
Q

What is a prediction in regards to association claims.

A
  • mathematically looking to the future…aka using an association to make our estimates more accurate.
24
Q

Predictions and + /- associations?

A
  • if we know the level of one variable we can more accurately guess or predict the level of the other variable.
  • ex: Heavy cell phone usage tied to poor sperm quality. If we known the amount of cell usage we can predict sperm quality.
25
Q

Are predictions from association claims perfect?

A
  • no usually they are off via certain margin
26
Q

When it comes to association claims and predictions, what makes them stronger/more accurate?

A
  • if there is a strong relationship btwn two variables = more accurate prediction
  • even if there is a slight association it helps us make predictions vs if we did not know about the association.
27
Q

With predicting association claims (+/-) if we know absolutely nothing about an association what will our predictions be based on?

A
  • average values
28
Q

Associations help us make predictions by reducing what?

A

the size of our prediction error

29
Q

Can Zero association claims help us make predictions?

A
  • NO
  • we cannot predict the lvl of one variable from the level of the other therefore our best bet is to guess the mean or avg.
30
Q

Explain what a causal claim is!

  • the variables ____
  • can be what three classifications
  • words that indicate causal ?
  • how are these held in comparison to other claims
  • tentative language that still means causal?
A
  • argue that one of the variables is responsible for CHANGING the either
  • the variables covary
  • can be +, - or curvilinear
  • cause, enhance, curb
  • hold these to higher standards
  • could, may seem, suggest, possible,potential
31
Q

What are the three steps to go from an association claim to a causal one?

A
  1. establish two variables are correlated (cannot have a zero relationship…..the cause variable and the outcome v)
  2. must show that the causal variable came first and the outcome v came last
  3. establish no other explanation exists for the relationship
32
Q

What are the four big validities?

A
  1. Construct
  2. External
  3. Statistical
  4. Internal
33
Q

Valid claim??

A
  • reasonable, accurate and justifiable

* never just say tis valid…we must specify the type

34
Q

What two validates apply to interrogating frequency claims?

A
  • Construct and External validity
35
Q

Frequency Claim:

- Construct Validity ?

A
  • how well did they measure their variables
    L> how well did the study measure or manipulate a variable
  • must establish that each variable has been measured reliably (similar scores on repeated testings) ad that the different lvld of a variable accurately correspond to the true differences.
36
Q

Frequency Claim:

- External Validity?

A
  • how well the results of the study generalize to or represent people and contexts besides those in the study itself!
  • ensure that participants rep the population they are suppose to
37
Q

What are the three types of validity that apply to interrogating Association Claims?

A
  1. Construct
  2. External
  3. Statistical
38
Q

Association Claim:

- Construct Validity?

A

-assess each variable
- how well were they measured
L> if well we can trust the conclusions

39
Q

Association Claim:

- External Validity?

A
  • can the association generalize to other populations? other contexts, times, places?
40
Q

Association Claim:

- Statistical Validity?

A
  • statistics are sued to describe data and estimate the probability that results can or cannot be attributed to chance
  • extent to which stat conclusions are accurate and reasonable
41
Q

Association Claim:
- Statistical Validity?
L> What two types of errors does good statistical validity minimize?

A
  1. Type I Errors: based on results concluding there is an association btwn 2 variables when there is none. (false alarm)
  2. Type II Errors: based on results conclude that there is one association when there is one. (Misses)
42
Q

Covariance??

A
  • As “A” changes, “B” changes
43
Q

What are the three rules for Causation?

A
  1. Covariance
  2. Temporal precedence: one variable came first in time before another variable
    EX: Music lessons enhance IQ…Music lessons must be proven to come first before IQ gains
  3. Internal Validity (third variable rule): a study should be able to rule out alternative explanations for the association.
44
Q

How do researchers attempt to support a causal claim?

A
  • experiment!
    L> gold standard of psychological research
    L> manipulate the variable they think is the cause and measure the variable they think is the effect.
  • Manipulated variable: IV
    -measured variable : DV
45
Q

How do experiments provide temporal precedence and internal validity for causal claims?

A
  • by manipulating one variable and measuring the other one can ensure that by manipulating the causal variable it came first.
    -can control for alt explanations (ensure internal v)
    L> ex: Random assignment: ensure participants are as similar as possible.
46
Q

Causal Claims:

  1. Does debt stress really cause health problems?
  2. Do family meals really curb eating disorders?
    * * are these right or wrong ?
A 
1. 
A)Covariance: established! (positive association) 
B)Temporal Precedence: NO 
C) Internal Validity? NO...alt explanations are possible.  
2. 
A) Covariance: YES
B) Temporal Precedence: NO
C) Internal Validity:  noooooo
47
Q

Causal Claims:

  1. External Validity
  2. Construct Validity
  3. Statistical Validity
A
  1. do the results generalize?
  2. interrogate both the manipulated and measured variable (how well they were measured)
    L>operationalizing manipulated variables one needs to create a specific task or situation that will represent each lvl.
  3. evaluate how well the design of the study allowed researchers to minimize the probability of making the relevant conclusion mistake a false alarm. How strong is the association?Is the difference statistically significant

Research Methods (10 decks)

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