PART.ONE:.MULTIPLE.REGRESSION| A psychiatrist wants to know whether the.level of pathology .(Path) in psychotic patient.6 months. after treatment can be predicted.with reasonable accuracy.from.knowledge of pretreatment. symptom ratings of thinking .disturbance .(Think dist) and.hostile.suspiciousness .(Host suspon. 53.patients. .We analyze the data using.SAS's.REG procedure and observe the results.shown in. Table.1. Based on those .findings, answer.the following questions. Multiple Linear Regression The REG Procedure Model: MODEL1 Dependent Variable: Path Number of Observations Read 53 Number of Observations Used 53 Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 2 2753.87136 1376.93568 6.24 0.0038 Error 50 11037 220.74597 Corrected Total 52 13791 Root MSE 14.85752 R-Square 0.1997 Dependent Mean 22.69811 Adj R-Sq 0.1677 Coeff Var 65.45708 Parameter Estimates Parameter Standard Variable DF Estimate Error t Value Pr > t Intercept 1 -0.63535 20.96833 -0.03 0.9759 Think_dist 1 23.45144 6.83851 3.43 0.0012 Host_susp -7.07261 3.01092 -2.35 0.02281)-Identify the dependent variable and the independent variables.in this study. .Also, state .the. Omnibus.Null and . Alternative.hypotheses. I 2)-Report.the test statistic.and.P-value.that should be used to test.the.Omnibus .(or.Overall) Null hypothesis. .What is your conclusion about the Omnibus .Null hypothesis?1 3)-Report and interpret the parameter estimates .for.Think dist and Host suspfrom the.SAS. output. T According to the output, which of the independent variables are significant predictors .for. level of pathology?T 4)-Using the regression equation, calculate the predicted.level of pathology . for a patient with a. score of thinking .disturbance.of.3.5.and.hostile.suspiciousness of.7..[Show .your.work and. wait to round.to.two.decimal places.until the end, after the math is done. ]1 5)-Interpret these findings (3-5.sentences.max). . Your answer.should .(1) restate.the.findings; and. (2).include an interpretation of the.R-square.value. 1PART.TWO: .LOGISTIC.REGRESSION| 102 patients with acute.myelogenous.leukemia .(AML) in remission were enrolled in a study of.a. new antisense oligonucleotide (asODN). .The patients were randomly assigned to receive a.10- day.infusion of .asODN-or.no.treatment (Control), and the effects.were.followed .for.90.days. .We. code the indicator variable.TRT=1 .for active.treatment.group and.TRT=0.for-control group. . Also, we record the time of remission (X, in months) from.diagnosis.or prior relapse at.study. enrollment, an important.covariate .in predicting relapse. .Relapse .(Y).is coded.as.1 .to .indicate. relapse, death, or major intervention, such as-bone marrow transplant.before .Day.90. .We want.to. investigate whether there is any evidence that administration of asODN.is associated with the. occurrence of an.AML .relapse. . We.analyze the.data .using.SAS's.LOGISTIC .procedure .and observe the results.shown.in.Table.2. .Based on those .findings, answer.the.following questions. ILogistic Regression The LOGISTIC Procedure Model Information Data Set WORK.AML Response Variable Y Number of Response Levels 2 Model binary logit Optimization Technique Fisher's scoring Number of Observations Read 102 Number of Observations Used 102 Response Profile Ordered Total Value Y Frequency 1 1 53 2 0 49 Probability modeled is Y=1. Model Convergence Status Convergence criterion (GCONV =1E-8) satisfied Model Fit Statistics Intercept and Criterion Intercept Only Covariates AIC 143.245 129.376 SC 145.870 137.251 -2 Log L 141.245 123.376Testing Global Null Hypothesis: BETA=0 Test Chi-Square DF Pr > ChiSq Likelihood Ratio 17.8687 2 0.0001 Score 16.4848 2 0.0003 Wald 14.0612 2 0.0009 Analysis of Maximum Likelihood Estimates Standard Wald Parameter DF Estimate Error Chi-Square Pr > ChiSq Intercept 2.6135 0.7149 13.3662 0.0003 TRT 1 -1. 1 191 0. 4669 5.7446 0.0165 X 1 -0. 1998 0.0560 12.7187 0.0004 Odds Ratio Estimates 95% Wald Effect Point Estimate Confidence Limits TRT 0.327 0. 131 0.815 X 0.819 0.734 0.914 Association of Predicted Probabilities and Observed Responses Percent Concordant 68.5 Somers' D 0.454 Percent Discordant 23.1 Gamma 0.496 Percent Tied 8.4 Tau-a 0.229 Pairs 2597 C 0.7271)-Identify the dependent variable and the independent variables.in this study. .Also, state.the Omnibus .Null and .Alternative.hypotheses. I 2)-Report the test-statistic.and.P-value.that should be used to test.the Omnibus.Null hypothesis. (i.e. "Global.Null"per-SAS). .What is your conclusion about the Omnibus.Null hypothesis?1 3)->Report.the odds ratios and .95% confidence.intervals.for.all.two.independent.variables. .Based. on those.confidence.intervals, which of the.independent variables are .significant predictors of decreasing relapse time (Y) and which ones are not significant predictors?.Be sure.to.include. the reasoning for your decisions. T 4)-Report p-values of the two independent variables.from the."Analysis of Maximum. Likelihood .Estimates" table in the SAS output. Based on the.P-values, which of the. independent variables are significant predictors of relapse .(Y) and which ones are not. significant predictors? Be sure to include the reasoning.for your decisions. ] 5)-In-3-4.sentences .(max), discuss what these findings .mean.from public health.perspective./]