Biostats Flashcards
what is nominal data?
categories are in an arbitrary order - no set order
ex: gender, ethnicity, marital status
what is ordinal data?
catergories are ranked in a logical order, but the difference between categories is not equal- ordered, ranked
ex: NYHA scale, 0-10 pain scale
Independent variable
-manipulated/changed by the investigator to determine effect on the dependent variable (outcome)
–> think study design (inclusion criteria, intervention/study drug)
Dependent variable
the outcomes being measured in a study
What is the null hypothesis?
Ho: states that there is no statistically significant difference between groups
–> this is what the researcher tried to disprove or reject
What is the alternative hypothesis?
Ha: states that there is a statically significant difference between the groups
–> this is what the researcher hopes to prove or accept
what is the alpha value and what does it means?
-researchers select a maximum possible error margin (5% , 0.05), comparing the p-value to alpha determined statistical significance
P < 0.05 = null hypothesis is REJECTED
P >/ 0.05 = null hypothesis ACCEPTED
what is a confidence interval?
provides the same information about significance as the P-value, plus the precision of the results
–> CI = 1 - alpha
Interpreting confidence intervals: comparing difference (means) data
-results statistically significant if the CI range does NOT include 0
ex: Difference (95% CI) : 38 (18-58) = sig
ex: Difference (95% CI) : 0.131 (-0.26- 0.89) = not sig
Interpreting confidence intervals: comparing ratio data (relative risk, odds ration, hazard ratio)
-result is statistically significant if the CI range does NOT include one
ex: Relative Risk : 0.92 (0.61-1.29) = not sig
ex: Relative Risk: 0.85 (0.72-0.99) = sig
Type 1 error
-null hypothesis is rejected in error
–> risk is determined by alpha and is related to the confidence interval
Cl = 1 - alpha (type 1 error)
Type 2 error
-null hypothesis is accepted in error
-probability denoted as beta (B) –> typically 0.1 or 0.2
-related to power (the probability of avoiding a type 2 error)
Power = 1- B
Relative Risk and Risk Ratio
Risk = (# of subjects with the unfavorable event) / (3 of subjects in that arm of the study)
RR = (risk in the treatment group) / (risk in the control group)
RR = 1 –> no difference in risk
RR > 1 –> higher risk in the treatment group
RR < 1 –> lower risk in the treatment group “as likely”
Relative Risk Reduction (RRR)
-how much the risk is reduced in the treatment group vs the control group –> “less likely)
RRR = (% risk control gr - % risk in tx gr) / (% risk in control group)
or
RRR= 1- RR
Absolute risk reduction (ARR)
- the absolute difference in outcome rates between 2 groups - more important to know
ARR = (% risk in the control group) - (% risk in the treatment group)
Interpretation: for every 100 pts treated with __, x fewer pts will have HF progression
Number needed to treat (NNT)
-number of ppl who need to be treated for a certain period of time in order for 1 patient to benefit
NNT= 1 / (risk in control group - risk in treatment group). OR
NNT = 1/ ARR
Rounding rules for NNT and NNH
-NNT: round up anything that is greater than a whole number (NNT = 52.1 –> 53)
-NNH: round down any number greater than a whole number ( NNH = 41.9 –> 41)
Number needed to harm (NNH)
-number of people who need to be treated for a certain period of time in order for 1 patient to experience harm ( an adverse event)
NNH = 1/ARR
Odds Ratio (OR)
-probability of an outcome occurring with an exposure versus without the exposure
OR = AD/BC
A: have the outcome, with exposure
B : dont have the outcome, without exposure
C: have the outcome, without exposure
D: dont have the outcome, without exposure
Hazard Ratio (HR)
-negative outcome measured in clinical trials
-rate at which an unfavorable event occurs within a short period of time
-assumes ratio is constant over time
-used in survival analysis
HR: (hazard rate in the tx group/ hazard rate in the control group)
Odds ratio and Hazard ratio interpretation
OR/HR =1, event rate in similar in both groups
OR/HR > 1: event rate is higher in the treatment group
OR/HR <1: event rate is lower in the treatment group
T-test
used when endpoints have continuous data and the data is normally distributed
-student t-test: used when the study has 2 independent samples: the tx group and the control group
Chi-squared/Fisher’s exact test
-used to determine statistical significance between treatment groups
ANOVA test
used to test for statistical significance when using continuous data with 3 or more samples or groups
