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University of Toronto St. George
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Anthropology
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ANT100Y1
(100)

Larry Sawchuk
(3)

Final

by
OneClass5431

Department

Anthropology

Course Code

ANT100Y1

Professor

Larry Sawchuk

Description

Assessing Etiology RISK FACTOR presentabsentassociationDISEASE yes noSTATISTICAL EVALUATION Odds RatioChi squareStratified Odds RatioHypothesis Testing Indicate whether the observed difference in the two groups can simply be attributed to chanceThe significance testaccept or rejectCommon elements are presented in summary form before the actual tests of significance The expression of the Disease is independent not associated of the specified Risk FactorCompare computed chi square observed to expected chi square critical valueIf chisquare value exceeds the expected reject the null hypothesis of no associationthere is an ASSOCIATIONCritical Chi Square ValueAllowing for 5 error in our decision OR 95 confident regarding the null hypothesis Step 1 State the HypothesesNull Hypothesis Ho A probabilistic statement about population parameter that is being tested by sampleHo always contains the equality statementA and B have no relationshipAlternative hypothesis H1Determined by the question implicit in the statement of the problemA and B have relationshipStep 2 Select the Level of Statistical SignificanceOnce the null hypothesis is stated a decision be1 Reject Ho 2 Accept Ho 3 Reserve judgement concerning Ho the decision is too close to call Step 3 Select the Appropriate Test StatisticDecide which test to use Depends on assuptionsChisquare Pearson 1900A nonparametric test whose model does not specify conditions about the parameters from which the sample was drawn However nonparametric tests still contain some assumptions Step 4 Define the Region of RejectionIn general a significance level of 05 or 01 is used in hypothesis testing a005 there are 5 chance in 100 that Ho will be rejected when it is actually true95 confident that we have made the correct decision about HoChisquare value vs critical chisquare with 1 dfDf of a test is defined by the sample size 1eg Z testOr the number of classes r1c 1 Odds ratio testStep 5 Compute the test statistic and assess HoIf the computed chi square value exceeds that expected at 005 level Observed relationship between the two factors is not likely to be due to chance factors alone 95 confident that the association between the two factors is not due to chance When one moves to the 01 level the critical chi square value necessarily becomes larger Step 6 Assess the meaning of your findingGenerate further hypotheses that follow from your assessment of initial HoChi square Rules of thumbWhole numbers only No zeroIn a 2 by 2if the total is less than 30 use fishers exactLess than 200 some suggest that you use continuity correction MH chisquareChi squareadbcN22NC1C2R1R2AssumptionsRandom sample data A sufficiently large sample size Type I error a true null hypothesis is incorrectly rejectedType II error one fails to reject a false null hypothesis No accepted cutoff Adequate cell sizes All cells of a 2by2 table and 5 or more in 80 of cells in larger tables but no cells with zero When this assumption is not met Yates correction is applied Independent observations Same observation can only appear in one cellChisquare cannot be used to test correlated data ex beforeafter matched pairs panel data All observation has the same underlying distribution Distribution is known in advance Nondirectional hypotheses Chisquare tests the hypothesis that two variables are related only by chance Finite values Normal distribution of deviations observed minus expected valuesChisquare is a nonparametric test in the sense that is does not assume the parameter of normal distribution for the dataonly for the deviations Data levelOdds RatioadbcYesNo Total YesAB AbNoC D Cd Total Ac Bd ABCD If OR is not equal to 1 there is an associationThe further away OR is the stronger the associationGeneral Guidelines for Interpreting Values of OR Value Effect of Exposure003 Strong negative0405 Moderate negative0608 Weak 0911 No effect 1216 Weak 1725 Moderate positiveor 26 Strong positive One Risk FactorStep 1 Simple comparisons between the Disease and various Risk VariablesGet ORsGet levels of significance Computed chisquares Possible RiskJudged to be Factors A sex Not significant Disease B smoke Not significant C diet Significant Ddrug Not significant Step 2 Data are then stratified for heterogeneityCompute OR with disease and Risk Factor C and then stratified by other Risk Factor AExamine the two ORs are they the sameEvaluate interactive chisquare value is greater than critical value assume interaction is present and there are differences in Disease and C depending on the level of strata

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