research 2

no implied categories
no value
no order
ex- race, sex
non parametric

adds meaning and order
rank
no equal distance
non parametric

0 is arbitrary
equal distance but no 0
ex- temperature
parametric

0 means something
ex- weight and pulse rate
parametric

consistency

accuracy

high reliability

how consistent raters evaluate or judge a IV

whether the measure is stable over time
measuring something multiple times yields a consistent value
gets closer to the truth
stability over time

how well the items on the measure work together to produce similar scores
internal consistency

pearson product correlation or pearson's r

pearson product correlation or pearson's r

ensure proper training among raters
protocols are clear
rating is consistent

sufficient number of questions
ensure questions are easily understood
increase your sample size

does a test look like what it is supposed to test

addresses how well test questions match the content or subject area they are intended to asses
opinion based

tells you how well a certain measure can predicts future behaviors or performance

the degree to which a construct measure converges with other measures that should be measuring the same thing

the degree to which a construct measure diverges from other measures that purport to be measuring something different

strength or magnitude

the natural deviations that occur when randomly sampling from the population
expect fluctuation

flawed sampling procedures whereby the researcher does not use a representative sample
not naturally occurring

random sampling error & bias

the distribution of a sample statistic that would be obtained if all possible samples of the same size were drawn from a given population

the mean of the sampling distribution will equal the mean of the population
as the sample size increases, the standard deviation of the sample distribution decreases

quantify whether a result is likely due to chance (random sampling error) or due to some factor of interest

no difference between the two groups

there is a difference

reject the null when there is actually no difference between the two groups/ alpha/ level of significance
(rejected and shouldn't have)

when we fail to reject a null when it is actually false (doesn't reject the null when you should've)
beta

the ability of the test to correctly reject a null when it is false

statistically sig and you reject the null

not statistically significant and fail to reject the null

standard error decreases and distributions become more clustered around the population statistic

not clinically or practically useful

statistical significance testing
effect size
confidence intervals

communicated by statistical significance by telling us how likely the current result would be if the null were true

communicated by effect size by telling us the magnitude of the experimental effect, or relationship, or odds between variables

communicated by confidence intervals by providing a range of plausible values for the population parameter being estimated

cohens d or hedges g
pearsons r or point biserial
odds ratio

standardized mean difference
estimate the magnitude of standardized differences between two group means

hedges g

0.0

+/- 0.2

+/- 0.5

+/- 0.8

correlation/association
measures the strength of a linear relationship between continuous variables

correlation/association
measure the strength of a relationship between one dichotomous and one continuous

0.0

+/- 0.1-0.3

+/- 0.3-0.5

+/- >0.5

proportion
ratio of the probability that an outcome occurs to the probability that the outcome does not occur

no difference

positively related

negatively related

the effect is real

if an effect occurred
if effect was positive or negative
the precision of the estimate

null = 0

null = 0

null = 1

subjects get 1 level of IV only, comparison is between different groups of same level

all subjects are in all levels and are compared against themselves

parametrical (ratio interval)

depth of a topic

breadth of a topic

how a theory is generated and constructed

how someone makes sense and or gives meaning to things that happen

describes aspects of a culture
researcher inserts themselves into the culture

confirmability, transferability, dependability, and credibility

findings are shaped by subjects and not researchers bias, motivation, or interest

showing that findings have applicability in other contexts
can they describe the context of the study?

findings are consistent and could be replicated

confidential
truth of the findings

transferability

confirmability

dependability

description of the decisions and steps researchers made through the project

working with others who have an impartial view as a way to uncover bias and test the hypothesis

multiple methods (sources or researchers) to confirm one common thing

cornerstone of qualitative research
spending time in the field to understand a culture, social setting, or interest

examining one's attitudes and judgments and how that affects the research process

moveable target
getting the same theme of information from multiple sources- saturated
interview till no more new information

trying to capture everything in an interview
looking for themes, topics
constantly compares

subjects POV

quantitative

structured

semi structured or unstructured

more conversational

leading

what events lead to
what was your life like

how did you feel about... when you first learned about it

how have your views changes
what is advice you would give to someone

a theme or topic and how people respond to each other

6-8 with a plus and minus margin of 2

40 year study about syphilis where subjects did not know they had syphilis and were not given treatments when it became available
subjects were not allowed to quite

1. established a commission to identify basic ethical principles
2. established the IRB

respect for persons
beneficence
justice

informed consent, privacy

risk/benefit assessment
minimize risks