perform hypothesis-testing methods to assess whether either treatment affects bl
ID: 3021246 • Letter: P
Question
perform hypothesis-testing methods to assess whether either treatment affects blood pressure or heart rate in patients with severe angina based on NIFED dataset.
Hint: need first to calculate the difference in blood pressure and heart rate between baseline and “Lv1” and then perform hypothesis testing. Compile your responses and a data output from all parts of this question.
Attached is NIFED dataset for HW #3.
Info about NIFED
Variable Column Description Code
-----------------------------------------------------------------------------
Id 1-2 ID
trtgrp 4 Treatment group N=nifedipine/P=placebo
bashrtrt 6-8 Baseline heart rate* beats/min
lv1hrtrt 10-12 Level 1 heart rate+ beats/min
lv2hrtrt 14-16 Level 2 heart rate beats/min
lv3hrtrt 18-20 Level 3 heart rate beats/min
bassys 22-24 Baseline systolic bp* mm Hg
lv1sys 26-28 Level 1 systolic bp mm Hg
lv2sys 30-32 Level 2 systolic bp mm Hg
lv3sys 34-36 Level 3 systolic bp mm Hg
-----------------------------------------------------------------------------
* Immediately prior to randomization.
+ Highest heart rate and systolic blood pressure at baseline and each level of
therapy respectively.
Values of 999 indicates that either
(a) the patient withdrew from the study prior to entering this level of therapy
(b) the patient achieved pain relief prior to reaching this level or therapy,
(c) the patient encountered this level of therapy, but this particular piece of data was missing.
NIFED Data SET
id trtgrp bashrtrt lv1hrtrt lv2hrtrt lv3hrtrt bassys lv1sys lv2sys lv3sys 1 P 60 70 64 999 128 110 120 999 2 N 52 64 98 999 180 156 160 140 3 P 100 94 999 999 190 140 999 999 4 N 84 88 96 112 136 126 122 110 5 P 56 70 61 64 230 150 130 150 6 P 105 120 999 999 142 150 999 999 7 N 116 116 999 999 210 230 999 999 8 N 68 68 72 84 170 150 150 156 9 P 85 88 90 92 150 134 140 154 10 N 64 60 999 999 140 120 999 999 11 N 76 90 999 999 160 164 999 999 12 N 88 125 140 999 150 140 140 999 13 P 88 78 80 72 130 120 108 118 14 P 96 114 999 88 152 144 999 158 15 P 54 60 52 58 100 100 92 110 16 P 60 62 68 60 170 180 206 188 17 N 56 58 56 60 110 112 102 110 18 N 56 60 999 999 120 120 999 999 89 N 54 60 78 76 125 120 118 118 20 N 60 60 999 999 230 170 999 999 21 P 60 54 60 64 100 120 130 116 22 N 92 100 100 100 124 134 146 180 23 P 72 84 84 999 168 178 140 999 24 N 100 96 999 999 110 116 999 999 25 P 100 90 113 999 150 130 128 999 26 N 52 74 88 66 164 144 128 140 27 N 76 76 999 999 170 170 999 999 28 P 75 75 75 88 152 152 150 150 29 P 58 58 58 58 999 999 999 999 30 N 56 54 999 59 106 124 999 120 31 P 70 60 999 999 160 180 999 999 32 N 51 66 999 999 150 136 999 999 33 P 90 98 999 999 180 180 999 999 34 N 90 86 999 999 160 140 999 999Explanation / Answer
Perform hypothesis-testing methods to assess whether either treatment affects blood pressure or heart rate in patients with severe angina based on NIFED dataset.
First we have to take two differences as,
i) X1 : difference between blood pressure and heart rate between baseline
ii) X2 : difference between blood pressure and heart rate between Lv1.
And we have to test the two means using t-test for two samples.
First we have to test variances are equal or not.
H0 : Variances are equal.
H1 : Variances are not equal.
Assume alpha = level of significance = 0.05
All the procedure we can done using MINITAB.
First enter data in MINITAB.
STAT --> Basic statistics --> 2 Variances --> select samples in different columns --> First : X1 --> Second --> X2 --> Options : confidence level --> 95.0 --> ok --> ok
Output is :
Test for Equal Variances: X1, X2
95% Bonferroni confidence intervals for standard deviations
N Lower StDev Upper
X1 34 119.211 152.239 208.951
X2 34 119.770 152.953 209.931
F-Test (normal distribution)
Test statistic = 0.99, p-value = 0.979
Levene's Test (any continuous distribution)
Test statistic = 0.00, p-value = 0.996
p-value = 0.979
p-value > alpha
Accept H0 at 5% level of significance.
Variances are equal.
We use pooled variance.
Hypothesis testing for two means :
H0: Means are equal.
H1 : At least one mean is different.
MINITAB steps for testing two means using t-test :
STAT --> Basic statistics --> 2-sample t --> samples in different columns --> First : X1 --> Second --> X2 --> click on assume equal variances --> options --> confidence level = 95.0 --> Test difference = 0 --> Alternative : not equal --> ok --> ok
Two-Sample T-Test and CI: X1, X2
Two-sample T for X1 vs X2
SE
N Mean StDev Mean
X1 34 103 152 26
X2 34 98 153 26
Difference = mu (X1) - mu (X2)
Estimate for difference: 4.58824
95% CI for difference: (-69.30453, 78.48100)
T-Test of difference = 0 (vs not =): T-Value = 0.12 P-Value = 0.902 DF = 66
Both use Pooled StDev = 152.5960
P-value > 0.05
Accept H0 at 5% level of significance.
Conclusion : At least one mean is different
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