Biostats 1

P = (number of exisiting cases of disease at a given point in time)/(total population)

P = incidence x duration

Number of new cases that occur during a period of time.

Proportion of people whop became diseased during a perior of time (probability/risk of disease during the period of time).

• Proportion of those with disease who tested positive
• Sensitivity = TP/(TP + FN)

• Proption of people without disease who test negative
• Specificity = TN/ (TN + FP)

• Proportion of people who test positive that are really diseased
• PPV = TP / (FP / TP)

• Proportion who test negative and really aren't diseased
• NPV = TN / (TN + FN)

changing disease incidence /prevalence

Stating that there is an effect or difference when none exists; p is probablility of making type 1 error

Stating that there is not an effect or difference when one exists;

Probablilty of getting the right answer to the study.

• Number of points in the population
• Differnece in complaince between groups
• Size of expected effect

Range of values in which a specified probability of the means are expected to fall.

• Interval includes 0 or 1 = H₀ is true
• Intervals overlap = not significantly different

Randomised controlled trial

Non-randomized controlled trial

Descriptive study

Analytical Study (cohort, case control, cross sectional)

• Analytical Study
• Taking an exposure group and looking forward for an outcome

Analytica study looking from an outcome back to evaluate for exposure

Looking at the exposure and outcome status at the same moment in time

• (r) bewtween -1 and +1
• The closer to +1 the stronger the correlation between the two variables

• r²
• this is the value that's reported

• Describe experience of individula/population
• First step in identification of new things
• 1. describe and evaluate trends in outcomes
• 2. provide data for panning
• 3. suggest new research

• Study of group characteristics; measure of association; non-comparative to another group
• Strengths: quick, cheap, easy
• Weaknesses: inability to link exposure and disease; lack of control over confounding factors

Inapporpriate inference from ecological data (relationship of groups doesn't mean relationship of individuals)

• Strengths: quick, cheap, establish "burden of diease"
• Weaknesses: confuses causation and correlation

• Strengths: evaluation of rare diseases with long latency, quick and cheap, multiple factors for a single disease
• Weakness: limited for rare exposures, no incidence rates, difficult to establish temporal relationship, prone to bias

• Rare exposures, good information collected
• Least bias, clear temporal relationship
• direct measurement of incidnce in exposed vs non-exposed

• Ineficient for rare diseases
• Expensive and time consuming
• Retrospectives are more vulnerable to bias

• controlled expeirment
• Randomization, blinidng, placebo controlled
• Cross over - each subject serves as their own control
• Factorial design - allows for evaluation of multiple hypothesises

Remove the risk (ie vaccination)

Early detection and treatment (ie, pap smear)

reduce complications of the disease (ie; insulin for diabetes)

• odds of being diseased if exposed: odds of being diseased if unexposed
• (A/B) / (C/D) = OR

• % increase of disease attrributabe to exposure
• 

• % differnce in diseased between normal and treated groups
• 

• The probability of getting diseased in exposeure group when compared to normal
• 

• % attributable of diseased to a factor (ie: 1/3 of pneumonia is caused by smoking)
• 

• Confidence Interval = (mean ±Z( σ /√N))
• Z = 2; σ = SD