Answered step by step
Verified Expert Solution
Link Copied!

Question

1 Approved Answer

$FL2@(#) IBM SPSS STATISTICS 64-bit MS Windows 23.0.0.0 #########################Y@30 May 1615:13:22Pain Medication Trials ###########################AGE ###Age in years########################TREATMEN ###Treatment ########################GENDER ####Gender ########################HEALTH ####General health ########################DOSAGE ####Dosage

$FL2@(#) IBM SPSS STATISTICS 64-bit MS Windows 23.0.0.0 #########################Y@30 May 1615:13:22Pain Medication Trials ###########################AGE ###Age in years########################TREATMEN ###Treatment ########################GENDER ####Gender ########################HEALTH ####General health ########################DOSAGE ####Dosage ########################STATUS ###Effect status ########################TIME ####Time to effect #################New drug ######?Existing drug #############################Male ######?#Female ##########################? #Poor #######@#Fair #######@#Good #############################Low ######?#High #############################Censored ######? Taken effect ####################DOCUMENT This data set concerns clinical trials for an in-development anti-inflammatory intended for arthritis patients. (Entered 29-Apr-2005) ############################################################# ################################ ########################################################### ##################\\###AGE=age TREATMEN=treatment GENDER=gender HEALTH=health DOSAGE=dosage STATUS=status TIME=time##############################################age:$@Role('0' )/treatment:$@Role('0' )/gender:$@Role('0' )/health:$@Role('0' )/dosage:$@Role('0' )/status:$@Role('0' )/time:$@Role('0' )################UTF-8#######ddfee433333? ddeeehddgeede#@eeedef433333?dedegdgfffff?edeedd? ddfde433333#@#@ddgde @defdedgfffff#@egdedd#@fdddee#@dedegegfffff#@edeede? gddfdegfffff#@ddfdd#@ddeeed?egdedd#@gdeddg433333? dedege#######@eddede433333#@defde?######?degde? ddfeed#@egdeddgfffff#@fdedeggfffff? eefddfdedegde#@degdegfffff#@#######@ddfde433333#@ddeeed433333#@efde de#@gdddef433333'@deddgd433333#@eddfdd333333#@kddfde433333? ddgde###### @degeed333333#@efdeddgfffff#@gdedee433333#@edddgd#@eddfdd433333? degee#######@#######@ddfee? degddd433333#@egdedd#@gedddg#@dedegdgfffff?edegde? ddgde#######@433333#@degdd333333#@ddfeed433333#@dfdedd? geeddf#@eedeed433333? dddfed#@ddgee433333#@#@ddgde433333#@defddd#@dfdddd @fedldeeeddege"@eddgee######?degddn? degedoddfddd#@dfdede @feefddgeedege#@edeeee433333#@deeddi#@ddgeegfffff#@ddgddd #@dgdedd333333"@feedef?dddeed"@eddfde###### @defeegfffff?###### @degee433333?deedddgfffff @egeedd@feeddg?eeddgegfffff#@eddgdegfffff? ddfee#@#@defee?ddgeed?dfeede#@feedef @eddege#@edefde#######@ddfed######? @edgee433333#@edgede#@egdeed#@edeeef? ededgd#@deegee#######@nedgdegfffff? eegdegfffff#@eegdde433333#@efddeegfffff&@geeedf? edeeed#@eedgde#@eegde? #@eefde433333#@edgeee?dfdeeegfffff#@edeedf? eeeedgeeeeged?edfde#@gfffff!@edgedgfffff#@eeedde @efeeee#@feeeeg#@eeeefe @deefde#######@eegdegfffff#@"@eefde433333#@edgdee#@dgeeedgfff ff#@fededg433333#@degeefdeeeefeeeefdej#######@edgde#@eeeeee######? efdeed#@gddeeg %@eeedge#@efeefddedfee#@#@eefdegfffff!@eefdejeeeeeee###### @geeeeg#@dejeefeeedgde#@eegdd###### @#@eeeeegfffff#@eegeee#@dfeded @edeedfgfffff#@eeeefdgfffff#@eededd433333#@eefde @#@eeede######? eefeee#######@dfdegedgdeedf433333#@deedfd#@dedede @edfde######?gfffff @eeeed433333#@edfdee433333#@dgdegedgedeef @deeegd?eeegde433333#@eegee433333? #@edgdeoedfeeegfffff#@efdded#@geefedfdeeefe#@eedfee ? edgee#@433333#@eefeegfffff#@eegdde&@dgeeee433333#@gedede#@ee keegdeedgeegfffff @edfde######?@ UNIANOVA time BY gender treatment /METHOD=SSTYPE(3) /INTERCEPT=INCLUDE /PLOT=PROFILE(treatment*gender) /EMMEANS=TABLES(OVERALL) /EMMEANS=TABLES(gender) /EMMEANS=TABLES(treatment) /EMMEANS=TABLES(gender*treatment) /PRINT=ETASQ HOMOGENEITY DESCRIPTIVE /CRITERIA=ALPHA(.05) /DESIGN=gender treatment gender*treatment. Univariate Analysis of Variance [DataSet1] C:\\Program Files\\IBM\\SPSS\\Statistics\\20\\Samples\\English\\pain_medication.sav Between-Subjects Factors Value Label Gender Treatment N 0 Male 99 1 Female 101 0 New drug 104 1 Existing drug 96 Descriptive Statistics Dependent Variable: Time to effect Gender Treatment Male New drug 3.7019 2.24823 54 Existing drug 4.5933 2.78195 45 Total 4.1071 2.53128 99 New drug 4.6320 2.91865 50 Existing drug 4.6078 2.74902 51 Total 4.6198 2.82007 101 New drug 4.1490 2.62135 104 Existing drug 4.6010 2.74991 96 Total 4.3660 2.68660 200 Female Total Mean Std. Deviation N Levene's Test of Equality of Error Variancesa Dependent Variable: Time to effect F df1 df2 2.491 3 Sig. 196 .061 Tests the null hypothesis that the error variance of the dependent variable is equal across groups. a. Design: Intercept + gender + treatment + gender * treatment Tests of Between-Subjects Effects Dependent Variable: Time to effect Type III Sum of Source Squares df Mean Square F Sig. Partial Eta Squared 32.665a 3 10.888 1.520 .210 .023 3826.791 1 3826.791 534.345 .000 .732 11.106 1 11.106 1.551 .215 .008 9.362 1 9.362 1.307 .254 .007 10.434 1 10.434 1.457 .229 .007 Error 1403.683 196 7.162 Total 5248.740 200 Corrected Total 1436.349 199 Corrected Model Intercept gender treatment gender * treatment a. R Squared = .023 (Adjusted R Squared = .008) Estimated Marginal Means 1. Grand Mean Dependent Variable: Time to effect 95% Confidence Interval Mean 4.384 Std. Error .190 Lower Bound 4.010 Upper Bound 4.758 2. Gender Dependent Variable: Time to effect 95% Confidence Interval Gender Mean Std. Error Lower Bound Upper Bound Male 4.148 .270 3.615 4.680 Female 4.620 .266 4.095 5.145 3. Treatment Dependent Variable: Time to effect 95% Confidence Interval Treatment Mean Std. Error Lower Bound Upper Bound New drug 4.167 .263 3.649 4.685 Existing drug 4.601 .274 4.061 5.140 4. Gender * Treatment Dependent Variable: Time to effect 95% Confidence Interval Gender Treatment Male New drug 3.702 .364 2.984 4.420 Existing drug 4.593 .399 3.807 5.380 New drug 4.632 .378 3.886 5.378 Existing drug 4.608 .375 3.869 5.347 Female Profile Plots Mean Std. Error Lower Bound Upper Bound GET FILE='C:\\Users\\padu\\AppData\\Local\\Temp\\1_Way_Between.sav'. DATASET NAME DataSet2 WINDOW=FRONT. SAVE OUTFILE='C:\\Users\\padu\\Documents\\Research methdods course documents\\IP820 Intermediate '+ 'Statistics Syllabus\\SPSS data\\1_Way_Between.sav_for lecture 8.sav' /COMPRESSED. DATASET ACTIVATE DataSet1. DATASET CLOSE DataSet2. GET FILE='C:\\Users\\padu\\AppData\\Local\\Temp\\2-WayBetween-SubjectsAnova.sav'. DATASET NAME DataSet3 WINDOW=FRONT. SAVE OUTFILE='C:\\Users\\padu\\Documents\\Research methdods course documents\\IP820 Intermediate '+ 'Statistics Syllabus\\SPSS data\\2-WayBetween-SubjectsAnova.sav_for lecture 8.sav' /COMPRESSED. GET FILE='C:\\Users\\padu\\AppData\\Local\\Temp\\1-WayWithin-SubjectsAnova.sav'. DATASET NAME DataSet4 WINDOW=FRONT. SAVE OUTFILE='C:\\Users\\padu\\Documents\\Research methdods course documents\\IP820 Intermediate '+ 'Statistics Syllabus\\SPSS data\\1-WayWithin-SubjectsAnova.sav_for lecture 8.sav' /COMPRESSED. DATASET ACTIVATE DataSet1. DATASET CLOSE DataSet4. GET FILE='C:\\Users\\padu\\AppData\\Local\\Temp\\2-WayWithin-SubjectsAnova.sav'. DATASET NAME DataSet5 WINDOW=FRONT. SAVE OUTFILE='C:\\Users\\padu\\Documents\\Research methdods course documents\\IP820 Intermediate '+ 'Statistics Syllabus\\SPSS data\\2-WayWithin-SubjectsAnova.sav_for lecture 8.sav' /COMPRESSED. DATASET ACTIVATE DataSet1. DATASET CLOSE DataSet5. DATASET ACTIVATE DataSet3. GET FILE='C:\\Program Files\\IBM\\SPSS\\Statistics\\20\\Samples\\English\\patient_los.sav'. DATASET NAME DataSet6 WINDOW=FRONT. DATASET ACTIVATE DataSet1. DATASET CLOSE DataSet6. DATASET ACTIVATE DataSet3. GET FILE='C:\\Users\\padu\\Documents\\Research methdods course documents\\IP820 Intermediate Statistics Syllabus\\SPSS data\\1-WayWithinSubjectsAnova.sav_for lecture 8.sav'. DATASET NAME DataSet7 WINDOW=FRONT. DATASET ACTIVATE DataSet1. DATASET CLOSE DataSet7. GET FILE='C:\\Users\\padu\\Documents\\Research methdods course documents\\IP820 Intermediate Statistics Syllabus\\SPSS data\\2-WayWithinSubjectsAnova.sav_for lecture 8.sav'. DATASET NAME DataSet8 WINDOW=FRONT. GET FILE='C:\\Users\\padu\\AppData\\Local\\Temp\\Ex8Q1.sav'. DATASET NAME DataSet9 WINDOW=FRONT. SAVE OUTFILE='C:\\Users\\padu\\Documents\\Research methdods course documents\\IP820 Intermediate '+ 'Statistics Syllabus\\SPSS data\\HW#6.sav' /COMPRESSED. DATASET ACTIVATE DataSet1. DATASET CLOSE DataSet9. SAVE OUTFILE='C:\\Users\\padu\\Documents\\Research methdods course documents\\IP820 Intermediate '+ 'Statistics Syllabus\\SPSS data\\pain_medication.sav_Unit 8 discussion.sav' /COMPRESSED

Step by Step Solution

There are 3 Steps involved in it

Step: 1

blur-text-image

Get Instant Access to Expert-Tailored Solutions

See step-by-step solutions with expert insights and AI powered tools for academic success

Step: 2

blur-text-image

Step: 3

blur-text-image

Ace Your Homework with AI

Get the answers you need in no time with our AI-driven, step-by-step assistance

Get Started

Recommended Textbook for

Holt Mcdougal Larson Algebra 2

Authors: HOLT MCDOUGAL

1st Edition 2012

9780547647159, 0547647158

More Books

Students also viewed these Mathematics questions