• Shuffle
Toggle On
Toggle Off
• Alphabetize
Toggle On
Toggle Off
• Front First
Toggle On
Toggle Off
• Both Sides
Toggle On
Toggle Off
Toggle On
Toggle Off
Front

### How to study your flashcards.

Right/Left arrow keys: Navigate between flashcards.right arrow keyleft arrow key

Up/Down arrow keys: Flip the card between the front and back.down keyup key

H key: Show hint (3rd side).h key

A key: Read text to speech.a key

Play button

Play button

Progress

1/87

Click to flip

### 87 Cards in this Set

• Front
• Back
 rates ratios and proportions often measure... dichotomous outcomes rates, rations and proportions are what type of measures? descriptive measures rate is.. frequency of event in specific time period what does finding risks for different subgroups allow for allows identification of high risk groups and possible clues of causality 4 components of rate numerator- freq denominator- population time period multiplier - / how many ratio is... relationship between numerator and denominator when they are unconnected quantities proportion is... numerator and denominator are always related often shown as percent equations rate ratio proportion rate- X / delta t ratio- X / Y proportion- X / Y+X Morbidity any departure from well being Mortality any departure from actually living...aka death morbidity measures are? 2types incidence and prevalence incidence number of new cases prevalence number of cases in population Cumulative incidence is proportion of population at risk that develops disease over specific peroid denominator must be observed entire duration followup Cumulative incidence equation is CI = number new cases dx during time ______________________ Pop at risk during same time Incidence rate is same shit only with diff length of folow up times Incidence rate equation Numberof new cases in specific time IR = __________________________ total person time of observation in pop at risk...huh Prevalence is number of existing cases in entire pop point prevalence is number of ppl w/ dx at single point in time _________________________ total number pop at that time period prevalence is number ppl w/ disease at any point during time peroid ______________________________ number of persons in pop incidence and prevalence think about it as... a bath tub.... incidence water going in prevelence water inside and death or recovery is how fast water leave and prevelance goes down Crude mortality rate is CMR total number deaths from all causes per 1000 persons during specific time ______________________ total number persons at that time Age specific mortality rate is ASMR total number of deaths from all causes in specific age group ___________________________ total number in that age group Cause specific mortality rate CSMR deaths from specific cause ________________________ total pop that period case fatality CF propensity of disease to cause death number deaths from dx _____________________ # ppl w/ dx proportionate mortality PM proportion of deaths from specific cause deaths from dx _________________ total deaths Association measuring is statistical relationship tween 2 or more variables Exposure vs Outcome exposure- potential causal characteristics (behavior or tx) outcome- consequence of behavior or tx how do we measure association risk ratio odds ratio risk ratio is risk of developing event in exposed individual to that of unexposed individual cumulative incidence exposed ________________________ cumulative incidence unexposed risk ration of 1 means? when does exposure show association? -risk is equal in exposed and unexposed groups -if greater than 1 than exposure is associated NOTE TO REMEMBER- for calculations with risk ratio recognize that total is for each group not whole study!!!! Odds ratio is.. ratio of number events and nonevents in cases to number of events and nonevents in control.... double positives * double negative __________________________ mixed * mixed OR greater than 1 means? what about less? greater- odds for event in exposed group higher less- event less liekly in exposed group Difference in descriptive and analytic epidemiology? analytic- tests predetermined hypotheses about association tween exposure and outcome variables hypothesis serves as framework for determining statistical significance null hypothesis... really how many times have we learned this now.... means no difference (for u morons out there) alternative hypothesis.. theres an association When type 1 and type 2 errors? wheres beta and alpha? ?]]when does power matter? I = P = positive II = N = negative power matters when null is rejected truthfully what is P value and what used for probability that effect as large as one seen in study could be from chance alone used to determine conclusion of study how do sample size and P value relate? inverse relationship sample up, P down normal P is... 0.05 to determine if findings significant what do we do once we have P value? use appropriate stat anal method compare calc value to table value at specified P value IF calc value larger...data significant what 4 tools are used to measure effects of interventions on outcomes relative risk reduction absolute risk reduction number needed to treat number neede to harm relative risk reduction extent to which exposure reduces a risk in comparison to unexposed proportion of risk in untreated group... RRR= (Ru - Re) / Ru or 1- RR absolute risk reduction simple...absolute value difference event rate of exposed and unexposed groups ARR = Re - Ru NOTE from what i understand these Re or Ru are cumulative incidence things descriptive statistics vs inferential stats D- methods and procedures for summarizing and describing data I- methods used to make statements about the populations based on sample attribute is specific value of variable ex female for gender requirements of variables.. exhaustive mutually exclusive Types of variable are Nominal Ordinal Interval Ratio Discrete vs continous Dependant vs independant What types of relationships can we have tween variables and what do they look like Negative Positive None Curvilinear - ex age vs intelligence True score theory takes into account the two components involved in measurement Observed score = true ability + random error random vs systematic error random- from factors that randomly effect measurement -not consistent effects -add variability w/o changing average -called noise Systematic -affect measurement across sample -positive or negative consistently -called bias reliability vs validity R- repeatability or consistency V- best availible approximation of the truth Types of validity External Construct Internal Conclusion External validity can we generalize this to other persons, places, times get a random large sample to get this construct validity are you using the correct instruments to measure what we are attempting to understand are we executing this correctly design wise internal validity do we see cause and effect is this the true cause or its it something else thats causing it conclusion validity to the results and findings match the conclusion given are we reading the data correctly and taking it into account 3 major characteristics of a variable distribution central tendency dispersion dispersion how to measure it spread of values around the central tendency range and standard deviation will show how certain scores relate to the mean of sample Statistical inference allows decision making information about hypotheisiszed values of an unknown parameter what kind of error is avoided and which can u not really help... systematic error avoided since it can be eliminated random error just kinda happens point estimates provide information on random error T/F F they do not... Confidence intervals interval estimation associating a measure statistical variation with a point estimate has two numerical values defining range of values covering parameter being estimated confidence interval better definition range of values around point estimate tween upper and lower limits how are precision and random error related inversely smaller random error more precise point estimate look at notes pages 34- 37 cuz i dont know wtf is going on there... do it how do we see relationships tween indepenant variables, control variables and dependant variables regression modelling! Continous outcome what kind of regression sued what association measure we get linear regression regression coefficient categorical (dichotomus) what kind associateion measure logistical odds ratio time to event..... cox regression hazard ratio.... (thats not what i heard in drug lit....) What are third variable effects? what are 3 types when other IV effect our results Confounding Mediation Moderation Confounding changes relationship related to both different interpretations when ignored or included mediator accounts for all or part of relationship IV causes interveneing variable in turn causes DV differs conceptually from mediation- confounder is not intermediate in causal sequence moderator alters strength or direction of relationship relationship is diff at diff lvls of moderator Medical utilization patterns effectiveness of therapy depends on therapy appropriate medication used as recommended suboptimal medication ultilization is the point below which desired effect is unlikely to be achieved Compliance extent behavoir coincides medical advice adhereance patients failure consume medication according to directions concordance agreement tween pt and HCP regarding ultilization behavior ISPOR does what... defines medical compliance conformity to recommendation dosing, timing, freq persistance length of time taking medication in time... What kinds of complaince are there initial noncompliance partial complinace compliance hypercompliance how can we measure complaince direct measures- directly observed therapy indirect measures- self report, provider esimates ethics contemporary emphasis on rights of ppl take risks to save themselves sumthing about IRBs and other ethical issues... dont care