Meta analysis Flashcards
7 steps of research for literature reviews
1: select research questions
2: selecting bibliographic databases
3: choosing search terms
4: applying practical screening criteria
5: applying methodological screening criteria
6: doing the review
7: synthesizing the results
validity in meta analyses depends on
reviewer’s expertise
critical imagination and quality of available literature
what step of research extends to numerical aggregation rather than having a qualitative focus
7 - synthesizing the results
reasons for meta study
power
reliability increase
noise reduction
practical design issues in individual studies
goals of meta analysis
estimate population effect
each study provides estimation so not sure about true effect
explain variabiity
steps of MA
1: objectives description
2: inclusion/ exclusion criteria
3: literature search
4: developing standardized protocol to evaluate quality of studies retrieved
5: coding form
6: meta analytic procedures
- pooling of study results
- testing for homogeneity of effect sizes
- selecting moderator variables
7: describe results, conclusions, limitations
how to deal with different effect sizes
translational scales for different measures of effect size
statistical goals of meta analysis
estimate combined ES
estimate confidence interval around ES
- variability within and between studies (s^2 and t^2)
explain variability between studies (potential moderators)
how do you combine effect sizes?
they dont have the same weight so dont average them
- instead you should give weight to larger studies and less weight to smaller ones as their evidence is less strong
fixed effect model
assumes there is true effect in population and all error is sampling error
study weight: w= 1/s^2
random effects model
study weight w=1/(s^2+t^2)
are studies homogeneous
test with Q-statistic
- is the between study variance
if p value is smaller alpha, then heterogeneous
- but with few studies there is a power problem
heterogeneity tests: some measures
t^2= estimated amount of heterogeneity (insensitive to number of studies and precision)
I^2= total heterogeneity
- not sensitive to number of studies
- not always adequate measure for heterogeneity
-suggested as criterion to go to subgroup or modertaro analysis
H^2= total variability, sampling variability
- ratio of SDof the estimated overall effect size from a random effects MA compared to SD of fixed effects MA
what bias do you have to be aware of in MA
publication bias
- file drawer problem
- accessibility bias
- duplication
- country/ language/ culture
statistical procedures against publication bias
- funnel plot by Eggers (plot effect sizes of studies against their precision)
- fail safe number, add z value of amount of studies that could be missing and see if still sig