Biostats-7

Question 1

Observational Studies

• what are they?
• Association or Causal?
• Ex.

Answer 1

• Natural course of events is just observed and recorded
• ONLY Association NOT causation

Examples:

• Case Series
• Cross-Sectional
• Ecological
• Case-control
• Cohort

Question 2

Experimental/Interventional

• what are they?
• Association or Causal?
• Ex.

Answer 2

• Investigator allocates exposure
• Can determine Causation

Examples:

• Randomized Controlled Trials
• Animal Trials

Question 3

What is the Gold Standard or Study Design?

Answer 3

Randomized, Double-Blind, Placebo Controlled Trial

Question 4

What is randomization?

- what is its purpose?

Answer 4

• If there are 2 treatments the patient should have an equal chance at either
• Ensures that treatment groups are equal on baseline (known) characteristics and unknown characteristics
• Eliminates Selection Bias
• GUARANTEES that the Statistical Significance Tests are valid

Question 5

What is a double blind trial?

Answer 5

Both investigator and subject are blinded to the exposure so that they do not influence the ascertainment of the outcome

Question 6

What is the purpose of trials being placebo controlled?

Answer 6

• Controls for Placebo Effect

- Helps to assess side affects

Question 7

What do you do in Intention to Treat Analysis?

- what if you don’t do this?

Answer 7

• Groups are analyzed according to original, randomized group regardless of whether they received the treatment or not
• By not doing this you introduce selection bias (this is important for accounting for unknown factors that may exist among groups)

Question 8

What is Type II error?

- when do people end up with Type II error?

Answer 8

• Null is not rejected when it should be

- Inadequate power leads to type II error

Question 9

What is power?

• what is the threshold?
• What determines power?

Answer 9

• Ability to detect an association or difference if it really exists (higher power is better chances of finding a treatment benefit)
• Power for a study should be over 80%
• Determined by SAMPLE SIZE (small sample = low power)
• Treatment effect
• Increasing the Alpha

Question 10

How do you calculate power?

Answer 10

Power = 1 - Beta error

Question 11

What is relative risk?

- when do you use it?

Answer 11

RR = Incidence in exposed group / Incidence in nonexposed group

• Measure of Association used in Clinical Trials

Question 12

How do you calculate incidence of disease in an exposed group?
- Non-exposed?

Answer 12

Incidence exposed = a/(a+b)

Incidence non-exposed = c/(c+d)

Therefore Relative Risk:
RR = [a/(a+b)]/[c/(c+d)]

Question 13

What is the risk difference?

- what kind of study is it used in?

Answer 13

RD = Incidence (exposed) - Incidence (unexposed)

Question 14

How do you calculate Number needed to treat?

- what does this tell you?

Answer 14

= 1/(risk difference)
= 1/ (incidence in placebo - incidence in treated)

**The number of patients you would need to treat with the drug before you saw a successful treatment

Question 15

What is validity?

Answer 15

Degree to which a measurement or study reaches a correct conclusion

Question 16

Differentiate between internal and external validity.

Answer 16

Internal Valdity:
- Extent to which the results of the study reflect the truth

External Validty:
- Extent to which the results of a study are applicable to other populations (generalizability)

Question 17

What is the difference between bias and confounding?

Answer 17

Bias:
- Systematic error that leads to a distortion of the results

Confouding:
- Mixing of the effect of an extraneous variable with the effects of the exposure and disease of interest

Question 18

What is type I error?

Answer 18

Error that occurs when the null hypothesis is true but it is incorrectly rejected

E.g. if significance level is determined to be 0.05 then 5% of the time null will be rejected when it shouldn’t be

Question 19

What determines the possibility of you having type I error in your experiment?

Answer 19

• alpha = level of signficance

**This is pre-determined by the investigator - how much error they are willing to accept

Question 20

What factors does internal validity rely on?

Answer 20

Chance
Bias
Confounding

Question 21

What does the P-value tell you?

Answer 21

Probability that the results are due to chance

**typically 0.05 or LESS

Question 22

What does a 95% confidence interval tell you?

Answer 22

Says that if you repeated the study 100 times then 95 of the values obtained will fall within that range

Question 23

What are some common confounders in studies?

Answer 23

• Age is common because it is associated with both disease and exposure
• Cigarette Smoking
• Alcohol Use
• Physical Activity
• BMI

Question 24

What are some ways to deal with confounding?

Answer 24

• Stratification by age, gender, smoking, etc.
• Statistical adjustment of the model
• RANDOMIZATION
• matching?

Question 25

What is the trade off between internal and external Validity?

Answer 25

Insuring internal validity may require that you exclude certain groups of patients (like those who are unlikely to adhere to the treatment)