POPH192 - Lecture 23

Question 1

what types of validity will a good study have?

Answer 1

both internal and external validity

Question 2

what is external validity

Answer 2

• do the findings apply to other populations?
• can these results ne generalised to another population of interest?
• external validity depends on the population group of the study

Question 3

what is internal validity?

Answer 3

is there a real association present in this study?
- are these results valid for the study population?

Question 4

what does internal validity depend on?

Answer 4

chance, bias and confounding

• are an alternative explanaion for why we got the results we did

Question 5

when is a study internally valid?

Answer 5

when the results of the study are not because of chance, confounding or bias

Question 6

what is chance a component on?

Answer 6

internal validity

Question 7

what is sampling?

Answer 7

• take a sample from a source population to do a study
• because it is impossible to do a study using the whole population

Question 8

what does the study sample give?

Answer 8

• an ‘estimate’ value of the population study
• this is the unknown true value of the measure that the study is trying to estimate

Question 9

what is sampling error?

Answer 9

sampling is unlikely to be perfect - due to chance

Question 10

what happens each time you sample?

Answer 10

each sample you take from the same population would be slightly different - due to chance

Question 11

what affect does chance have on the population?

Answer 11

because of chance, the study might not be an accurate representation of the population

Question 12

what is chance?

Answer 12

a random sampling error
- most common reason for this is a small sample size

Question 13

how do you reduce the likelihood of chance?

Answer 13

• increase sample size

Question 14

what are the affects of increasing sample size?

Answer 14

1) reduces the sample variability
2) increases the likelihood of having a representative sample
3) increases the precision of the parameter estimate

Question 15

how could you evaluate chance?

Answer 15

to decide if results are due to chance (or actually true), you can use confidence intervals and p-values

Question 16

what is a 95% confidence interval?

Answer 16

we are 95% sure that our true population parameters lies between the bounds of the confidence interval

Question 17

what is the interpretation of the confidence interval?

Answer 17

we are 95% sure that our true population parameter lies between upper bound** and **lower bound

Question 18

what affects the precision of the 95% confidence interval?

Answer 18

-indicated by width of confidence interval

wide CI = smaller sample size = less precision

narrow CI = larger sample size = more precision

Question 19

what is clinical importance?

Answer 19

it is a level set in RCT

• to decide if the intervention has a real, genuine and noticeable effect on daily life

Question 20

what is considered ‘not clinically important’?

Answer 20

anything above the clincical importance threshold of 0.9 (reduction of 10%)

or

• the entire CI is above the level of clinical importance

Question 21

what is considered ‘clinically important’?

Answer 21

• anything below 0.9 is clincally important

OR

• the entire confidence interval has to be below the level of clinical importance

Question 22

what happens when the threshold is crossed?

Answer 22

it is considered ‘possibly clincally important’

• as we don’t know if the parameter is above or below threshold

Question 23

is clincal importance the same as statistical significance?

Answer 23

no