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93 Cards in this Set
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define epidemiology

atudy of occurence and distribution of diseases in POPULATION


clinical approach vs publich health approach
epi is a metho of which one? 
clinical individual level
public health studies disease at population epi is method of public healthpop. 

epi's 3 factors

host
agent environment 

define environment

all other factors inhibit OR promote disease transmiss.


agents

obvious ones, then u got genetic traits, chemicals, radiation


some of the host factors

personal behaviors
immunization status physicologic states(preg) puberty 

environmental factors

physicalweather, geology
biologicalfood, water, air social + cultural crowding, war 

what did epidimiologist start out focusing on?
what are they focused on now 
in past infectous diseases
nowchronic diseases 

infectous diseases are characterized by

single, known identifiable cause


pharmacoepi studies what

drug use patterns, drug use effects, and adverse drug effects


whats whats diff in adverse event and adverse drug reaction

adv event error while pt is taking med, but doesn't necess. mean it caused event
drug reaction outcome thats harmful or unpleasenttheres a casual link to drug 

define side effect
medication error 
S.E dose dep effect predicatble + maybe desirable or undesirable
Med Errrrany preventable event may cause harm to pt 

FDA uses what to approve new drug
phase1 2 3 
Clinical trials
1determines safety 2small groupfor intended pts, tests efficacy 3thousands of pts, RCT, 14 yrs 

limitations of clinical trials

only studies on hundreds/thousnads of pplrare SE will show later
can't see long term effex decay effect efficacy vs effectivness 

whats decay effect?
efficacy vs effectivness? 
decayovertime effect decre. trial can't show this
efficacy intended effect doesn't necessarily have effectivness (out of study ppl will have compliance issues) 15 tabs/day 

define postmarketing surveillance

needed to see long term effects of drugs
means of gathering data about product after approval 

T or F
some drugs need to do phase 4 clinical trials AFTER approval 
True


examples of pharmacovigilance

medwatchinfo on serious SE reported by HCP
VAERS vaccine A.E. 

define pharmacovigilance

science of detecting, assessing, and preventing A.E. of meds


whats ultimate goal in establishing relationships between drugs and outcomes

establishin a casual relationhip (casuality)


whats criteria for causality

1) correlationconsist pattern of change
2) temporal ordering 3)rule out alternative explanations 

whats internal validity

approx truth of inferences for causeeffect relationships


what kind of variable is independent

predictor its variable being manipulated durr


what kind of varibale is dependent

outcome whatever result of changing indep durr again


define confounding

extraneous varibale that correlates with indep and dep variable (unforseen correlation factor)
need to control for this 

type 1 error

false positive
null is true but reject null 

type 2

false negative
null is false but accept null 

define sampling

selecting units(ppl) from population so you can later generalize results back to population


random selection

different units are selected by chance


parameter vs statistics

paramean if you were able to sample entire POPULATION
statistic value estimated from sample data 

obsv vs experiment study

obsvno intervention or exp
exp manipulation of factor(exposure) and randomization of ppl 

in regards to data collection
define primary define secondary give examples 
primaryinvestigator is 1st to collect info
medical exams, interviews, observations seondary data collected by OTHERS of other purposes than study medical/employ records, census data 

define a study design

translate conceptual hypothesis into operational one


goal of study may be? (3)

exploratory when knowledge is poor, small scale
descriptivefrom hypothesis, excross sect, case study analyticaltest hypotheses, ex case control, RCT, cross sect. 

spectrum for causality

estab. casGen hypothesis
RCT>Cohort>casecontrol>cross sect. 

observational design
types 
alt to exp design, good for drug use patten+ outcomeS.E.
1)case reportclinical exp of 1 pt on drug 2)case series same but mult. pts 

case series are of value cuz they

study cases of similar disease
and give clinical education, audit and resarch value 

give an example of case series mentioned in class

HIV epidemic
dr's saw pts with kaposi's sarcoma but not in normal pts(mediaterrian men with cancer) 

whats an ecologic study
whats missing in this design 
utilizes aggregate data or combine data with individual data
missin relationship btwn exposure and outcome at individual level(incomplete design) study must be interpreted carefully to avoid eco fallacy 

define ecological fallacy

taking aggregate data and applying to specific individuals
CAD higher in richer cities 

cross sectional study

disregards length of time (done at 1 pt in time)
provide estimates of prevalence of condition but not incidence useful in developing new hypothesis not causuality(cause inabillity to determine if exposure was before outcome) 

casecontrol study
whens it useful? 
useful in rare outcomes
study sample of ppl with cancer and group without outcome of interest as control temporal order of exp + outcome is paramount** 

whats a common element used in casecontrol to avoid possible confounding
drawbacks of casecontrol 
matching
misclassifaction selection bias recall bias 

longitudinal study

2 or MORE observations are collected for every unit in study
offer ability to see changes in study unity and across units 

2 studies used widely in epidemiology

casecontrol
cohort 

whats common application of cohort

used when its unethical or impossible to intentionally expose pt to drug or intervention


cohort drawbacks
viewed as 
exp+time consuming
not for rare outcomes as modified approach to RCTbut no random assign 

TEMPLES neighbor OSMAR isnt trying to find job, TEMPLES thinks all hispanics are lazy (true story)
is this ecological fallacy? 
NO
individual>group = stereotype group>individual= ecolog fallacy 

what are traditional epidemiologic studies

observational no intervention or tx


Random assigment?
yes no 
if yesexperiemntal
if no, is there control grp or multiple measures? if yesquasi exper. no nonexp(observ.) 

experimental designs are G.S. in terms of establishing...

internal validity


random selection vs random assignment

rand sel collecting ppl from population to sample (external validity)
rand assign 2 grps will preform same, any diff is cuz chance determines internal validity 

experimental design classified into

signal to noise approach
signalrelated to key variable tying to measure noiseall factors(confounders) make it hard to see signal want signal to be higher than noise 

T or F
increasing the signal is better than decreasing the noise 
F
they both increase the quality of research 

signalenhancing designs are called...
whats prototypical factorial design 
factorial designs
RCT 

what are 2 major types of noisereducing designs

covariance and blocking designs


for assignment to group, what does:
R, N,C stand for 
Rrandom
Nnonequal grps Ccutoff 

is everyone in a factorial design (2x2) getting same tx?

No
some get X11, others get X22 

for a 2x2..how many factors are there?
for a 2x2x3 how many factors? 
2 factors(prolly dose + duration)
3 factors 

how many levels are there in 2x2?
2x2x3? how many groups? 
F12, F22= 4 groups
F12, F22, F33= 12 groups 

if we are given a preintervention test and score avg is 90....what is the score once the pts are broken up into groups

about same approx 90


what is the null effect

its situation where diferent tx combos have NO effect
all scores for tx and setting =90 

for a factorial design of 3x3x2 how many effects will there be

there will be 3 effects,
there is 1 effect for every factor 

whats a main effect
vs a interaction effect 
main you look at 1 factor at time + # in particular lvl is lower than any number(regardless of lvl) it has main interac on outcome variable
if no level with the lowest # the factor has interaction effect on outcome 

RCT most commonly studies info abou...

ADV. DRUG RXS and EFFICACY or EFFECTIVNESS of healthcare services or health technologies(med dev, surgery)


randomization ensures equal distibution of

confounders


main goal of randomized block design
what kind of strategy is this? 
to reduce noise or variance in data
analytical it doesnt affect anything with research participants, it groups ppl in data analysis 

you can't do a block design unless

you collected data on potenetial confounders


what seperates regression discountinuity (quasi experimentl design) apart from other prepost designs

method of participants are assigned to condidtions
assigned based on cutoff score or preprogram measure 

what are steps in doing a regression discontinuity design

1 measure QOL for everyone pre and post w/o txing
2set cutofftx ppl <50QOL, and no tx >50QOL 3 see if results <50QOL line moved up or down compared to the line for >50QOL 

what is the difference between the cutoff groups regression lines

its the discontinuity...its in the regression lines at the cutoff point


what is a maturation threat
how to correct 
something that changes naturally (exkids taking math class in school+ tutoring)
is tutoring helping or is it really learning over time form school add a control group ROXO (orig study)  ROXO tutoring grp ROO non tutoring 

how do you address an instrumentation threat

ROXO
ROOXO add another observation exkids learn prof always has B as answer do new study with both exams being B, then change last exam randomly 

correlation indicates
its purpose 
degree of association btwn 2 variables, "r" but not if one caused the other
to make a prediction about 1 variable based on known v. 

what are 2 correlation directions

positive x incr. y incr
negative xin and y dec. education + prejudice 

positive r
negative 1 is a negative # strong or weak? 
01
10 doesn't indicate strength, just look at number (.8>.2) 

does correlation establish causation?

No
need temporal order, correlation, and rule out alt 

pearsons correlation coefficient (r) determines

stregnth and direction btwn x and y, measured at INTERVAL LEVLS


steps to do a correlation problem

1) calc r..make sure denom is done by summing (xx1)^2 each the multiply total by total y^2
2) calc t value 3) compare t value to table, if > then its statis signif. 

what are requirements for using pearsons r

straight line
interval data random sample normally distributed x + y 

simple regression analysis

like correlation, but we are interested in seeing if changes in x CAUSES change in y


what is R^2

coeffiecent of determination
its % of variance x(dep) accounted by variablitiy in y(indep) 

what are residuals

HINT** its not the left over cum on your moms mouth
diff btwn predicted values and actual value of dependent variable (y) errors we can't predict 

error =
what does a + error mean 
Y(actual value)  y^(predicted)
+ means y^ is under predicting  is over predict compared to Y 

if you don't know x
how do you determine error 
_
Y(actual) y (avg) 

if you have x
how do you determine error 
y(actual) y^(predicted)


how do you determine SStotal

you do this when don't know x
its the numerator in r or _ E(yy) ^2 

how do you determine SSerror

this is done when you know what x is
E(yy^ )^2 

what the equation for SSreg

SSreg= SStotal  SSerror


whats equation for Proporionate reduction in error or PRE

SSreg/ SStotal


how do you determine r2
and what does it express 
well can do r squared
or find PRE and then put in percentage it expresses % of variance in y explained by x 

how do you test statistical sig of regression coeff (r^2)

SSreg/dfreedom (1)
 SSerror/ N2 this is equal to F, compare this umber to Ftable to determine sig or not 

steps in making a simple regressio formula

1)use formula to determine b(slope) SP/SSx and intercept a=y(avg) bx(avg)
2) make new tableuse x to determine y^(predicted) 3)do SStotal equat and SSerror (its y new predicted) 4) find SStotal 5) calc PRE = r2 6) calc F and compare to table to determine signif. 