1.Describe the characteristics of the people included in the sample at the baseline examination.
2. Characterize the people who had casual serum glucose >200 mg/dL at the baseline examination and compare them to people who had ≤200 mg/dL casual serum glucose at the baseline examination in terms of age, body mass index (BMI), education and whether they were taking blood pressure medication at the time of the baseline examination.
3. 3.Are the results from the bivariate comparisons above (point 2) different if the actual casual serum glucose level at baseline examination is analysed, rather than the dichotomized glucose variable?
4.Considering only individuals with casual serum glucose level at baseline below 200 mg/dL, which of these variables (age, BMI, education and whether they were taking blood pressure medication) are significantly associated with casual serum glucose level at baseline in a multivariable analysis? Describe their relationship with casual serum glucose level, including which variables explain the most variation in casual serum glucose level. Report the ‘minimum model’ obtained. Explain any differences you observe between the results of the bivariate analysis in point 3 above and multivariable analysis.
Baseline Examination Data
At the baseline examination, data from 3950 people were collected in terms of sex, education level, age, Serum total cholesterol, Systolic blood pressure, Diastolic blood pressure, Current cigarette smoking, Number of cigarettes smoked each day, Body mass index, use of anti-hypertensive medication, Casual serum glucose. Out of 3950, 1725 are male and 2225 are female. 41.1 % people are education level 0-11 years where as 28.6% are diploma holder. 49.1 % people are currently smoker at baseline examination whereas 50.1% are not currently smoker. Only 3.1% people use anti hyper tension mediation. At baseline examination, mean serum total cholesterol is 237.41mmg/dL with standard deviation 44.779. Mean age of people at baseline examination is 49.95 years with standard deviation 8.644 years. Mean systolic blood pressure is 132.838 mmHg with standard deviation 22.3993. Mean systolic blood pressure is 83.047 mm/Hg with standard deviation 12.0522. People averagely smoke 8.87 cigarettes every day with standard deviation 11.844. At baseline examination people have average BMI 25.8523 Kg/m2 with standard deviation 4.07827. Mean casual serum glucose is observed as 82.18 mmg/dL with standard deviation 24.485.
2. We group the variable in two categories:
1: casual serum glucose >200 mg/dL at the baseline examination
2 : casual serum glucose 200 mg/dL at the baseline examination
Following table shows the descriptive statistics for the group 1 and 2 for age and BMI
|
Descriptive Statistic |
Age at baseline exam (years) |
Body Mass Index at baseline exam (kg/m^2) |
||
|
Group 1 |
Group 2 |
Group 1 |
Group 2 |
|
|
Mean |
55.71 |
49.94 |
28.3565 |
25.8425 |
|
Size |
31 |
3556 |
31 |
3556 |
|
Median |
56 |
49 |
28.5 |
25.425 |
|
Variance |
45.28 |
74.613 |
31.245 |
16.388 |
|
Std. Deviation |
6.729 |
8.638 |
5.58969 |
4.04821 |
|
Minimum |
43 |
32 |
17.17 |
15.54 |
|
Maximum |
67 |
70 |
43.67 |
56.8 |
|
Range |
24 |
38 |
26.5 |
41.26 |
|
Interquartile Range |
10 |
14 |
7.39 |
4.99 |
|
Skewness |
-0.249 |
0.199 |
0.407 |
0.961 |
|
Kurtosis |
-0.79 |
-1.014 |
0.76 |
2.507 |
We have 31 people having casual serum glucose >200 mg/dL at the baseline examination and 3556 people having casual serum glucose 200 mg/dL at the baseline examination. Mean age of people having casual serum glucose >200 mg/dL at the baseline examination is 55.71 (6.729) years whereas mean age of people having casual serum glucose 200 mg/dL at the baseline examination is 49.94(8.638) years. BMI of group 1 is higher than group 2. One can observed the difference between other statistic from above table.
64.51 % people having casual serum glucose >200 mg/dL at the baseline examination has education 0-11 years whereas for other group this percentage is 42.28%. In Group 1 19.35% people are diploma holder whereas in Group 2 29.33% people are diploma holders. There is no one in Group 1 which has college degree or more whereas in Group 2 about 12% people have college degree or more.
9% People in group 1 taking mediation whereas only 3% people in Group 2 are taking medication for controlling the blood pressure.
3 No, the results from the bivariate comparisons above (point 2) different if the actual casual serum glucose level at baseline examination is analysed, rather than the dichotomized glucose variable.
Grouping of Variables and Descriptive Statistics
4. We considered the individuals with casual serum glucose level at baseline below 200 mg/dL. There are 3568 people having casual serum glucose level at baseline below 200 mg/dL. To test whether there is any significant relation between the casual serum glucose level at baseline and independent variables (age, BMI, education and whether they were taking blood pressure medication). We run the multiple regression analysis. In the independent variables Education and whether they were taking blood pressure medication are categorical variables, we need to create dummy variables for testing the above hypothesis, we create four dummy variables (3 for education and 1 for whether they were taking blood pressure medication. We take 1-11 years education and not taken any medication as a reference variable.
Following table shows the ANOVA of multiple regression analysis:
|
Source of Variation |
Sum of Squares |
df |
Mean Square |
F |
P- Value |
|
Regression |
16607.05 |
6 |
2767.842 |
12.84 |
0 |
|
Residual |
765023.7 |
3549 |
215.56 |
||
|
Total |
781630.7 |
3555 |
The P-value = 0 suggest that there is significant relation between the casual serum glucose level at baseline and independent variables (age, BMI, education and whether they were taking blood pressure medication). That is at least one of the coefficient is non zero. From following table we can see that which coefficient are significant or not.
|
Independent Variable |
Coefficient |
Std. Error |
t |
P Value |
|
(Constant) |
63.485 |
2.197 |
28.899 |
0.000 |
|
Age at baseline exam (years) |
0.192 |
0.030 |
6.471 |
0.000 |
|
Body Mass Index at baseline exam (kg/m^2) |
0.289 |
0.062 |
4.640 |
0.000 |
|
HighSchoolDiploma |
-0.097 |
0.612 |
-0.159 |
0.873 |
|
Some College and Vocation |
-0.399 |
0.729 |
-0.547 |
0.584 |
|
degree and more |
-0.087 |
0.822 |
-0.106 |
0.916 |
|
taken or not |
-0.772 |
1.423 |
-0.542 |
0.588 |
We can see that only age and BMI are significant whereas other variables education and whether they were taking blood pressure medication are found to be non-significant for predicting the casual serum glucose level at baseline. Both age and BMI have positive correlation with casual serum glucose level at baseline.
As the education and whether they were taking blood pressure medication are found to be non-significant for predicting the casual serum glucose level at baseline, we fit the model again using age and BMI variables only. Following is the equation of multiple regression analysis for predicting the casual serum glucose level at baseline using age and BMI as a predictor variables.
Casual serum glucose level at baseline = 63.35 + 0.192 × Age + 0.29 × BMI
Each incline in age results in 0.192 incline in casual serum glucose level whereas each unit of BMI incline results in 0.29 incline in casual serum glucose level.
From bivariate analysis, we observed that mean age and BMI for person having casual serum glucose >200 mg/dL at the baseline examination is more than the person having casual serum glucose 200 mg/dL at the baseline examination. And from the multivariate analysis we observed that each icline in age and BMI results in incline in the casual serum glucose level.
Multiple Regression Analysis
5. We carry the paired t test for the testing whether there is casual serum glucose level change significantly between the baseline examination and the follow-up examination. We observed t statistics is -1.854 and P- value is 0.064 < 0.1 suggest that there is significant change in the casual serum glucose level change significantly between the baseline examination and the follow-up examination at 10% level of significance.
We now group the people having casual serum glucose >200 mg/dL and casual serum glucose 200 mg/dL. After that we used paired t test for both the groups.
We observed t statistics is 3.124 and P- value is 0.008 < 0.1 suggest that there is significant change in the casual serum glucose level >200 mg/dL change significantly between the baseline examination and the follow-up examination at 10%.
We observed t statistics is -2.675 and P- value is 0.008 < 0.1 suggest that there is significant change in the casual serum glucose level 200 mg/dL change significantly between the baseline examination and the follow-up examination at 10%.
From the test statistics we can observed that glucose level increases for people having casual serum glucose level >200 mg/dL at baseline examination and glucose level decreases for people having casual serum glucose level <= 200 mg/dL at baseline examination.
SPSS Output:
|
Sex |
|||||
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
||
|
Valid |
Male |
1725 |
43.7 |
43.7 |
43.7 |
|
Female |
2225 |
56.3 |
56.3 |
100.0 |
|
|
Total |
3950 |
100.0 |
100.0 |
||
|
Education level |
|||||
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
||
|
Valid |
0-11 years |
1625 |
41.1 |
42.2 |
42.2 |
|
High school diploma |
1131 |
28.6 |
29.4 |
71.6 |
|
|
Some college, vocational school |
638 |
16.2 |
16.6 |
88.2 |
|
|
College degree or more |
456 |
11.5 |
11.8 |
100.0 |
|
|
Total |
3850 |
97.5 |
100.0 |
||
|
Missing |
System |
100 |
2.5 |
||
|
Total |
3950 |
100.0 |
|||
|
Current cigarette smoking at baseline exam |
|||||
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
||
|
Valid |
Not current smoker |
2009 |
50.9 |
50.9 |
50.9 |
|
Current smoker |
1941 |
49.1 |
49.1 |
100.0 |
|
|
Total |
3950 |
100.0 |
100.0 |
||
|
Use of anti-hypertensive medication at baseline exam |
|||||
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
||
|
Valid |
Not currently used |
3771 |
95.5 |
96.8 |
96.8 |
|
Current use |
124 |
3.1 |
3.2 |
100.0 |
|
|
Total |
3895 |
98.6 |
100.0 |
||
|
Missing |
System |
55 |
1.4 |
||
|
Total |
3950 |
100.0 |
|||
|
casual serum at baseline exam |
|||||
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
||
|
Valid |
1 |
3568 |
90.3 |
99.1 |
99.1 |
|
2 |
32 |
.8 |
.9 |
100.0 |
|
|
Total |
3600 |
91.1 |
100.0 |
||
|
Missing |
System |
350 |
8.9 |
||
|
Total |
3950 |
100.0 |
|||
|
Descriptive Statistics |
|||
|
N |
Mean |
Std. Deviation |
|
|
Age at baseline exam (years) |
3950 |
49.95 |
8.644 |
|
Systolic blood pressure at baseline exam (mmHg) |
3950 |
132.838 |
22.3993 |
|
Diastolic blood pressure at baseline exam (mmHg) |
3950 |
83.047 |
12.0522 |
|
Number of cigarettes smoked each day at baseline exam |
3920 |
8.87 |
11.824 |
|
Body Mass Index at baseline exam (kg/m^2) |
3932 |
25.8523 |
4.07827 |
|
Serum total cholesterol at baseline exam (mmg/dL) |
3904 |
237.41 |
44.779 |
|
Casual serum glucose at baseline exam (mg/dL) |
3600 |
82.18 |
24.485 |
|
Valid N (listwise) |
3552 |
||
|
Case Processing Summary |
|||||||
|
NewVar |
Cases |
||||||
|
Valid |
Missing |
Total |
|||||
|
N |
Percent |
N |
Percent |
N |
Percent |
||
|
Age at baseline exam (years) |
1 |
31 |
96.9% |
1 |
3.1% |
32 |
100.0% |
|
2 |
3556 |
99.7% |
12 |
.3% |
3568 |
100.0% |
|
|
Body Mass Index at baseline exam (kg/m^2) |
1 |
31 |
96.9% |
1 |
3.1% |
32 |
100.0% |
|
2 |
3556 |
99.7% |
12 |
.3% |
3568 |
100.0% |
|
|
Education level * NewVar Crosstabulation |
||||
|
Count |
||||
|
NewVar |
Total |
|||
|
1 |
2 |
|||
|
Education level |
0-11 years |
20 |
1470 |
1490 |
|
High school diploma |
6 |
1020 |
1026 |
|
|
Some college, vocational school |
5 |
572 |
577 |
|
|
College degree or more |
0 |
415 |
415 |
|
|
Total |
31 |
3477 |
3508 |
|
|
Use of anti-hypertensive medication at baseline exam * NewVar Crosstabulation |
||||
|
Count |
||||
|
NewVar |
Total |
|||
|
1 |
2 |
|||
|
Use of anti-hypertensive medication at baseline exam |
Not currently used |
29 |
3402 |
3431 |
|
Current use |
3 |
113 |
116 |
|
|
Total |
32 |
3515 |
3547 |
|
|
Case Processing Summary |
|||||||
|
casual serum at baseline exam |
Cases |
||||||
|
Valid |
Missing |
Total |
|||||
|
N |
Percent |
N |
Percent |
N |
Percent |
||
|
Age at baseline exam (years) |
1 |
3556 |
99.7% |
12 |
.3% |
3568 |
100.0% |
|
2 |
31 |
96.9% |
1 |
3.1% |
32 |
100.0% |
|
|
Body Mass Index at baseline exam (kg/m^2) |
1 |
3556 |
99.7% |
12 |
.3% |
3568 |
100.0% |
|
2 |
31 |
96.9% |
1 |
3.1% |
32 |
100.0% |
|
|
Descriptives |
|||||
|
casual serum at baseline exam |
Statistic |
Std. Error |
|||
|
Age at baseline exam (years) |
1 |
Mean |
49.94 |
.145 |
|
|
95% Confidence Interval for Mean |
Lower Bound |
49.66 |
|||
|
Upper Bound |
50.22 |
||||
|
5% Trimmed Mean |
49.82 |
||||
|
Median |
49.00 |
||||
|
Variance |
74.613 |
||||
|
Std. Deviation |
8.638 |
||||
|
Minimum |
32 |
||||
|
Maximum |
70 |
||||
|
Range |
38 |
||||
|
Interquartile Range |
14 |
||||
|
Skewness |
.199 |
.041 |
|||
|
Kurtosis |
-1.014 |
.082 |
|||
|
2 |
Mean |
55.71 |
1.209 |
||
|
95% Confidence Interval for Mean |
Lower Bound |
53.24 |
|||
|
Upper Bound |
58.18 |
||||
|
5% Trimmed Mean |
55.81 |
||||
|
Median |
56.00 |
||||
|
Variance |
45.280 |
||||
|
Std. Deviation |
6.729 |
||||
|
Minimum |
43 |
||||
|
Maximum |
67 |
||||
|
Range |
24 |
||||
|
Interquartile Range |
10 |
||||
|
Skewness |
-.249 |
.421 |
|||
|
Kurtosis |
-.790 |
.821 |
|||
|
Body Mass Index at baseline exam (kg/m^2) |
1 |
Mean |
25.8425 |
.06789 |
|
|
95% Confidence Interval for Mean |
Lower Bound |
25.7094 |
|||
|
Upper Bound |
25.9756 |
||||
|
5% Trimmed Mean |
25.6369 |
||||
|
Median |
25.4250 |
||||
|
Variance |
16.388 |
||||
|
Std. Deviation |
4.04821 |
||||
|
Minimum |
15.54 |
||||
|
Maximum |
56.80 |
||||
|
Range |
41.26 |
||||
|
Interquartile Range |
4.99 |
||||
|
Skewness |
.961 |
.041 |
|||
|
Kurtosis |
2.507 |
.082 |
|||
|
2 |
Mean |
28.3565 |
1.00394 |
||
|
95% Confidence Interval for Mean |
Lower Bound |
26.3061 |
|||
|
Upper Bound |
30.4068 |
||||
|
5% Trimmed Mean |
28.1757 |
||||
|
Median |
28.5000 |
||||
|
Variance |
31.245 |
||||
|
Std. Deviation |
5.58969 |
||||
|
Minimum |
17.17 |
||||
|
Maximum |
43.67 |
||||
|
Range |
26.50 |
||||
|
Interquartile Range |
7.39 |
||||
|
Skewness |
.407 |
.421 |
|||
|
Kurtosis |
.760 |
.821 |
|||
|
Use of anti-hypertensive medication at baseline exam * NewVar Crosstabulation |
||||
|
Count |
||||
|
NewVar |
Total |
|||
|
1 |
2 |
|||
|
Use of anti-hypertensive medication at baseline exam |
Not currently used |
29 |
3402 |
3431 |
|
Current use |
3 |
113 |
116 |
|
|
Total |
32 |
3515 |
3547 |
|
|
Descriptives |
|||||
|
NewVar |
Statistic |
Std. Error |
|||
|
Age at baseline exam (years) |
1 |
Mean |
55.71 |
1.209 |
|
|
95% Confidence Interval for Mean |
Lower Bound |
53.24 |
|||
|
Upper Bound |
58.18 |
||||
|
5% Trimmed Mean |
55.81 |
||||
|
Median |
56.00 |
||||
|
Variance |
45.280 |
||||
|
Std. Deviation |
6.729 |
||||
|
Minimum |
43 |
||||
|
Maximum |
67 |
||||
|
Range |
24 |
||||
|
Interquartile Range |
10 |
||||
|
Skewness |
-.249 |
.421 |
|||
|
Kurtosis |
-.790 |
.821 |
|||
|
2 |
Mean |
49.94 |
.145 |
||
|
95% Confidence Interval for Mean |
Lower Bound |
49.66 |
|||
|
Upper Bound |
50.22 |
||||
|
5% Trimmed Mean |
49.82 |
||||
|
Median |
49.00 |
||||
|
Variance |
74.613 |
||||
|
Std. Deviation |
8.638 |
||||
|
Minimum |
32 |
||||
|
Maximum |
70 |
||||
|
Range |
38 |
||||
|
Interquartile Range |
14 |
||||
|
Skewness |
.199 |
.041 |
|||
|
Kurtosis |
-1.014 |
.082 |
|||
|
Body Mass Index at baseline exam (kg/m^2) |
1 |
Mean |
28.3565 |
1.00394 |
|
|
95% Confidence Interval for Mean |
Lower Bound |
26.3061 |
|||
|
Upper Bound |
30.4068 |
||||
|
5% Trimmed Mean |
28.1757 |
||||
|
Median |
28.5000 |
||||
|
Variance |
31.245 |
||||
|
Std. Deviation |
5.58969 |
||||
|
Minimum |
17.17 |
||||
|
Maximum |
43.67 |
||||
|
Range |
26.50 |
||||
|
Interquartile Range |
7.39 |
||||
|
Skewness |
.407 |
.421 |
|||
|
Kurtosis |
.760 |
.821 |
|||
|
2 |
Mean |
25.8425 |
.06789 |
||
|
95% Confidence Interval for Mean |
Lower Bound |
25.7094 |
|||
|
Upper Bound |
25.9756 |
||||
|
5% Trimmed Mean |
25.6369 |
||||
|
Median |
25.4250 |
||||
|
Variance |
16.388 |
||||
|
Std. Deviation |
4.04821 |
||||
|
Minimum |
15.54 |
||||
|
Maximum |
56.80 |
||||
|
Range |
41.26 |
||||
|
Interquartile Range |
4.99 |
||||
|
Skewness |
.961 |
.041 |
|||
|
Kurtosis |
2.507 |
.082 |
|||
DATASET COPY Q4.
DATASET ACTIVATE Q4.
FILTER OFF.
USE ALL.
SELECT IF (NewVar=2).
DATASET ACTIVATE DataSet1.
EXECUTE.
DATASET ACTIVATE Q4.
DATASET ACTIVATE DataSet1.
SAVE OUTFILE='C:UsersRaju ChavanDownloadsassignment stats.sav' /COMPRESSED.
DATASET ACTIVATE Q4.
SAVE OUTFILE='C:UsersRaju ChavanDesktopRR.xlsx' /COMPRESSED.
DATASET ACTIVATE DataSet1.
DATASET ACTIVATE DataSet1.
DATASET CLOSE Q4.
DATASET COPY Q4.
DATASET ACTIVATE Q4.
FILTER OFF.
USE ALL.
SELECT IF (NewVar=2).
DATASET ACTIVATE DataSet1.
EXECUTE.
DATASET ACTIVATE Q4.
RECODE educ (2=1) (ELSE=0) INTO Edu1.
VARIABLE LABELS Edu1 'HighSchoolDiploma'.
EXECUTE.
RECODE educ (3=1) (ELSE=0) INTO Vocation.
VARIABLE LABELS Vocation 'Some College and Vocation'.
EXECUTE.
RECODE SEX (4=1) (ELSE=0) INTO Degree.
VARIABLE LABELS Degree 'College Degree and more'.
EXECUTE.
RECODE BPMEDS.1 (1=1) (ELSE=0) INTO Meditation.
VARIABLE LABELS Meditation 'taken or not'.
EXECUTE.
|
Variables Entered/Removedb |
|||
|
Model |
Variables Entered |
Variables Removed |
Method |
|
1 |
taken or not, HighSchoolDiploma, Body Mass Index at baseline exam (kg/m^2), degree and more, Age at baseline exam (years), Some College and Vocationa |
. |
Enter |
|
a. All requested variables entered. |
|||
|
b. Dependent Variable: Casual serum glucose at baseline exam (mg/dL) |
|||
|
Model Summary |
||||
|
Model |
R |
R Square |
Adjusted R Square |
Std. Error of the Estimate |
|
1 |
.146a |
.021 |
.020 |
14.682 |
|
a. Predictors: (Constant), taken or not, HighSchoolDiploma, Body Mass Index at baseline exam (kg/m^2), degree and more, Age at baseline exam (years), Some College and Vocation |
||||
|
ANOVAb |
||||||
|
Model |
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
|
1 |
Regression |
16607.050 |
6 |
2767.842 |
12.840 |
.000a |
|
Residual |
765023.664 |
3549 |
215.560 |
|||
|
Total |
781630.714 |
3555 |
||||
|
a. Predictors: (Constant), taken or not, HighSchoolDiploma, Body Mass Index at baseline exam (kg/m^2), degree and more, Age at baseline exam (years), Some College and Vocation |
||||||
|
b. Dependent Variable: Casual serum glucose at baseline exam (mg/dL) |
||||||
|
Coefficientsa |
||||||
|
Model |
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
||
|
B |
Std. Error |
Beta |
||||
|
1 |
(Constant) |
63.485 |
2.197 |
28.899 |
.000 |
|
|
Age at baseline exam (years) |
.192 |
.030 |
.112 |
6.471 |
.000 |
|
|
Body Mass Index at baseline exam (kg/m^2) |
.289 |
.062 |
.079 |
4.640 |
.000 |
|
|
HighSchoolDiploma |
-.097 |
.612 |
-.003 |
-.159 |
.873 |
|
|
Some College and Vocation |
-.399 |
.729 |
-.010 |
-.547 |
.584 |
|
|
degree and more |
-.087 |
.822 |
-.002 |
-.106 |
.916 |
|
|
taken or not |
-.772 |
1.423 |
-.009 |
-.542 |
.588 |
|
|
a. Dependent Variable: Casual serum glucose at baseline exam (mg/dL) |
||||||
|
ANOVAb |
||||||
|
Model |
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
|
1 |
Regression |
16477.435 |
2 |
8238.717 |
38.257 |
.000a |
|
Residual |
765153.279 |
3553 |
215.354 |
|||
|
Total |
781630.714 |
3555 |
||||
|
a. Predictors: (Constant), Body Mass Index at baseline exam (kg/m^2), Age at baseline exam (years) |
||||||
|
b. Dependent Variable: Casual serum glucose at baseline exam (mg/dL) |
||||||
|
Coefficientsa |
||||||
|
Model |
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
||
|
B |
Std. Error |
Beta |
||||
|
1 |
(Constant) |
63.350 |
2.009 |
31.526 |
.000 |
|
|
Age at baseline exam (years) |
.192 |
.029 |
.112 |
6.679 |
.000 |
|
|
Body Mass Index at baseline exam (kg/m^2) |
.290 |
.061 |
.079 |
4.727 |
.000 |
|
|
a. Dependent Variable: Casual serum glucose at baseline exam (mg/dL) |
||||||
|
Paired Samples Statistics |
|||||
|
Mean |
N |
Std. Deviation |
Std. Error Mean |
||
|
Pair 1 |
Casual serum glucose at baseline exam (mg/dL) |
81.04 |
2824 |
20.073 |
.378 |
|
Casual serum glucose at follow-up exam (mg/dL) |
81.83 |
2824 |
22.270 |
.419 |
|
|
Paired Samples Correlations |
||||
|
N |
Correlation |
Sig. |
||
|
Pair 1 |
Casual serum glucose at baseline exam (mg/dL) & Casual serum glucose at follow-up exam (mg/dL) |
2824 |
.438 |
.000 |
|
Paired Samples Test |
|||||||||
|
Paired Differences |
t |
df |
Sig. (2-tailed) |
||||||
|
Mean |
Std. Deviation |
Std. Error Mean |
95% Confidence Interval of the Difference |
||||||
|
Lower |
Upper |
||||||||
|
Pair 1 |
Casual serum glucose at baseline exam (mg/dL) - Casual serum glucose at follow-up exam (mg/dL) |
-.785 |
22.513 |
.424 |
-1.616 |
.045 |
-1.854 |
2823 |
.064 |
|
Paired Samples Statistics |
|||||
|
Mean |
N |
Std. Deviation |
Std. Error Mean |
||
|
Pair 1 |
Casual serum glucose at baseline exam (mg/dL) |
271.36 |
14 |
69.373 |
18.541 |
|
Casual serum glucose at follow-up exam (mg/dL) |
211.00 |
14 |
64.709 |
17.294 |
|
|
Paired Samples Correlations |
||||
|
N |
Correlation |
Sig. |
||
|
Pair 1 |
Casual serum glucose at baseline exam (mg/dL) & Casual serum glucose at follow-up exam (mg/dL) |
14 |
.420 |
.135 |
|
Paired Samples Test |
|||||||||
|
Paired Differences |
t |
df |
Sig. (2-tailed) |
||||||
|
Mean |
Std. Deviation |
Std. Error Mean |
95% Confidence Interval of the Difference |
||||||
|
Lower |
Upper |
||||||||
|
Pair 1 |
Casual serum glucose at baseline exam (mg/dL) - Casual serum glucose at follow-up exam (mg/dL) |
60.357 |
72.298 |
19.322 |
18.613 |
102.101 |
3.124 |
13 |
.008 |
|
Paired Samples Statistics |
|||||
|
Mean |
N |
Std. Deviation |
Std. Error Mean |
||
|
Pair 1 |
Casual serum glucose at baseline exam (mg/dL) |
80.10 |
2810 |
14.186 |
.268 |
|
Casual serum glucose at follow-up exam (mg/dL) |
81.19 |
2810 |
19.887 |
.375 |
|
|
Paired Samples Correlations |
||||
|
N |
Correlation |
Sig. |
||
|
Pair 1 |
Casual serum glucose at baseline exam (mg/dL) & Casual serum glucose at follow-up exam (mg/dL) |
2810 |
.231 |
.000 |
|
Paired Samples Test |
|||||||||
|
Paired Differences |
t |
df |
Sig. (2-tailed) |
||||||
|
Mean |
Std. Deviation |
Std. Error Mean |
95% Confidence Interval of the Difference |
||||||
|
Lower |
Upper |
||||||||
|
Pair 1 |
Casual serum glucose at baseline exam (mg/dL) - Casual serum glucose at follow-up exam (mg/dL) |
-1.090 |
21.598 |
.407 |
-1.889 |
-.291 |
-2.675 |
2809 |
.008 |
References:
Abbott, M. L. (2016). Using Statistics in the Social and Health Sciences with SPSS and Excel. John Wiley & Sons.
Bickel, P. J., & Doksum, K. A. (2015). Mathematical statistics: basic ideas and selected topics, volume I (Vol. 117). CRC Press.
Chatterjee, S., & Hadi, A. S. (2015). Regression analysis by example. John Wiley & Sons.
Darlington, R. B., & Hayes, A. F. (2016). Regression analysis and linear models: Concepts, applications, and implementation. Guilford Publications.
Draper, N. R., & Smith, H. (2014). Applied regression analysis (Vol. 326). John Wiley & Sons.
Fox, J. (2015). Applied regression analysis and generalized linear models. Sage Publications.
Glantz, S. A., Slinker, B. K., & Neilands, T. B. (2016). Primer of applied regression & analysis of variance. McGraw-Hill Medical Publishing Division.
Paired T-test for Glucose Level Change
Larson-Hall, J. (2015). A guide to doing statistics in second language research using SPSS and R. Routledge.
Pett, M. A. (2015). Nonparametric statistics for health care research: Statistics for small samples and unusual distributions. Sage Publications.
Pett, M. A. (2015). Nonparametric statistics for health care research: Statistics for small samples and unusual distributions. Sage Publications.
Rasch, D., & Schott, D. (2018). Basic Ideas of Mathematical Statistics. Mathematical Statistics, 1-38.
Schroeder, L. D., Sjoquist, D. L., & Stephan, P. E. (2016). Understanding regression analysis: An introductory guide (Vol. 57). Sage Publications.
Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics. Allyn & Bacon/Pearson Education.
At the baseline examination, data from 3950 people were collected in terms of sex, education level, age, Serum total cholesterol, Systolic blood pressure, Diastolic blood pressure, Current cigarette smoking, Number of cigarettes smoked each day, Body mass index, use of anti-hypertensive medication, Casual serum glucose. Out of 3950, 1725 are male and 2225 are female. 41.1 % people are education level 0-11 years where as 28.6% are diploma holder. 49.1 % people are currently smoker at baseline examination whereas 50.1% are not currently smoker. Only 3.1% people use anti hyper tension mediation. At baseline examination, mean serum total cholesterol is 237.41mmg/dL with standard deviation 44.779. Mean age of people at baseline examination is 49.95 years with standard deviation 8.644 years. Mean systolic blood pressure is 132.838 mmHg with standard deviation 22.3993. Mean systolic blood pressure is 83.047 mm/Hg with standard deviation 12.0522. People averagely smoke 8.87 cigarettes every day with standard deviation 11.844. At baseline examination people have average BMI 25.8523 Kg/m2 with standard deviation 4.07827. Mean casual serum glucose is observed as 82.18 mmg/dL with standard deviation 24.485.
- Characterize the people who had casual serum glucose >200 mg/dL at the baseline examination and compare them to people who had ≤200 mg/dL casual serum glucose at the baseline examination in terms of age, body mass index (BMI), education and whether they were taking blood pressure medication at the time of the baseline examination.
We group the variable in two categories:
1: casual serum glucose >200 mg/dL at the baseline examination
2 : casual serum glucose 200 mg/dL at the baseline examination
Following table shows the descriptive statistics for the group 1 and 2 for age and BMI
|
Descriptive Statistic |
Age at baseline exam (years) |
Body Mass Index at baseline exam (kg/m^2) |
||
|
Group 1 |
Group 2 |
Group 1 |
Group 2 |
|
|
Mean |
55.71 |
49.94 |
28.3565 |
25.8425 |
|
Size |
31 |
3556 |
31 |
3556 |
|
Median |
56 |
49 |
28.5 |
25.425 |
|
Variance |
45.28 |
74.613 |
31.245 |
16.388 |
|
Std. Deviation |
6.729 |
8.638 |
5.58969 |
4.04821 |
|
Minimum |
43 |
32 |
17.17 |
15.54 |
|
Maximum |
67 |
70 |
43.67 |
56.8 |
|
Range |
24 |
38 |
26.5 |
41.26 |
|
Interquartile Range |
10 |
14 |
7.39 |
4.99 |
|
Skewness |
-0.249 |
0.199 |
0.407 |
0.961 |
|
Kurtosis |
-0.79 |
-1.014 |
0.76 |
2.507 |
We have 31 people having casual serum glucose >200 mg/dL at the baseline examination and 3556 people having casual serum glucose 200 mg/dL at the baseline examination. Mean age of people having casual serum glucose >200 mg/dL at the baseline examination is 55.71 (6.729) years whereas mean age of people having casual serum glucose 200 mg/dL at the baseline examination is 49.94(8.638) years. BMI of group 1 is higher than group 2. One can observed the difference between other statistic from above table.
64.51 % people having casual serum glucose >200 mg/dL at the baseline examination has education 0-11 years whereas for other group this percentage is 42.28%. In Group 1 19.35% people are diploma holder whereas in Group 2 29.33% people are diploma holders. There is no one in Group 1 which has college degree or more whereas in Group 2 about 12% people have college degree or more.
9% People in group 1 taking mediation whereas only 3% people in Group 2 are taking medication for controlling the blood pressure.
- Are the results from the bivariate comparisons above (point 2) different if the actual casual serum glucose level at baseline examination is analysed, rather than the dichotomized glucose variable?
No, the results from the bivariate comparisons above (point 2) different if the actual casual serum glucose level at baseline examination is analysed, rather than the dichotomized glucose variable.
- Considering only individuals with casual serum glucose level at baseline below 200 mg/dL, which of these variables (age, BMI, education and whether they were taking blood pressure medication) are significantly associated with casual serum glucose level at baseline in a multivariable analysis? Describe their relationship with casual serum glucose level, including which variables explain the most variation in casual serum glucose level. Report the ‘minimum model’ obtained. Explain any differences you observe between the results of the bivariate analysis in point 3 above and multivariable analysis.
We considered the individuals with casual serum glucose level at baseline below 200 mg/dL. There are 3568 people having casual serum glucose level at baseline below 200 mg/dL. To test whether there is any significant relation between the casual serum glucose level at baseline and independent variables (age, BMI, education and whether they were taking blood pressure medication). We run the multiple regression analysis. In the independent variables Education and whether they were taking blood pressure medication are categorical variables, we need to create dummy variables for testing the above hypothesis, we create four dummy variables (3 for education and 1 for whether they were taking blood pressure medication. We take 1-11 years education and not taken any medication as a reference variable.
Following table shows the ANOVA of multiple regression analysis:
|
Source of Variation |
Sum of Squares |
df |
Mean Square |
F |
P- Value |
|
Regression |
16607.05 |
6 |
2767.842 |
12.84 |
0 |
|
Residual |
765023.7 |
3549 |
215.56 |
||
|
Total |
781630.7 |
3555 |
The P-value = 0 suggest that there is significant relation between the casual serum glucose level at baseline and independent variables (age, BMI, education and whether they were taking blood pressure medication). That is at least one of the coefficient is non zero. From following table we can see that which coefficient are significant or not.
|
Independent Variable |
Coefficient |
Std. Error |
t |
P Value |
|
(Constant) |
63.485 |
2.197 |
28.899 |
0.000 |
|
Age at baseline exam (years) |
0.192 |
0.030 |
6.471 |
0.000 |
|
Body Mass Index at baseline exam (kg/m^2) |
0.289 |
0.062 |
4.640 |
0.000 |
|
HighSchoolDiploma |
-0.097 |
0.612 |
-0.159 |
0.873 |
|
Some College and Vocation |
-0.399 |
0.729 |
-0.547 |
0.584 |
|
degree and more |
-0.087 |
0.822 |
-0.106 |
0.916 |
|
taken or not |
-0.772 |
1.423 |
-0.542 |
0.588 |
We can see that only age and BMI are significant whereas other variables education and whether they were taking blood pressure medication are found to be non-significant for predicting the casual serum glucose level at baseline. Both age and BMI have positive correlation with casual serum glucose level at baseline.
As the education and whether they were taking blood pressure medication are found to be non-significant for predicting the casual serum glucose level at baseline, we fit the model again using age and BMI variables only. Following is the equation of multiple regression analysis for predicting the casual serum glucose level at baseline using age and BMI as a predictor variables.
Casual serum glucose level at baseline = 63.35 + 0.192 × Age + 0.29 × BMI
Each incline in age results in 0.192 incline in casual serum glucose level whereas each unit of BMI incline results in 0.29 incline in casual serum glucose level.
From bivariate analysis, we observed that mean age and BMI for person having casual serum glucose >200 mg/dL at the baseline examination is more than the person having casual serum glucose 200 mg/dL at the baseline examination. And from the multivariate analysis we observed that each icline in age and BMI results in incline in the casual serum glucose level.
- Did the casual serum glucose level change significantly between the baseline examination and the follow-up examination? Is this result the same when casual serum glucose level is categorised according to the clinical threshold of >200 mg/dL versus ≤200 mg/dL?
We carry the paired t test for the testing whether there is casual serum glucose level change significantly between the baseline examination and the follow-up examination. We observed t statistics is -1.854 and P- value is 0.064 < 0.1 suggest that there is significant change in the casual serum glucose level change significantly between the baseline examination and the follow-up examination at 10% level of significance.
We now group the people having casual serum glucose >200 mg/dL and casual serum glucose 200 mg/dL. After that we used paired t test for both the groups.
We observed t statistics is 3.124 and P- value is 0.008 < 0.1 suggest that there is significant change in the casual serum glucose level >200 mg/dL change significantly between the baseline examination and the follow-up examination at 10%.
We observed t statistics is -2.675 and P- value is 0.008 < 0.1 suggest that there is significant change in the casual serum glucose level 200 mg/dL change significantly between the baseline examination and the follow-up examination at 10%.
From the test statistics we can observed that glucose level increases for people having casual serum glucose level >200 mg/dL at baseline examination and glucose level decreases for people having casual serum glucose level <= 200 mg/dL at baseline examination.
SPSS Output:
|
Sex |
|||||
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
||
|
Valid |
Male |
1725 |
43.7 |
43.7 |
43.7 |
|
Female |
2225 |
56.3 |
56.3 |
100.0 |
|
|
Total |
3950 |
100.0 |
100.0 |
||
|
Education level |
|||||
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
||
|
Valid |
0-11 years |
1625 |
41.1 |
42.2 |
42.2 |
|
High school diploma |
1131 |
28.6 |
29.4 |
71.6 |
|
|
Some college, vocational school |
638 |
16.2 |
16.6 |
88.2 |
|
|
College degree or more |
456 |
11.5 |
11.8 |
100.0 |
|
|
Total |
3850 |
97.5 |
100.0 |
||
|
Missing |
System |
100 |
2.5 |
||
|
Total |
3950 |
100.0 |
|||
|
Current cigarette smoking at baseline exam |
|||||
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
||
|
Valid |
Not current smoker |
2009 |
50.9 |
50.9 |
50.9 |
|
Current smoker |
1941 |
49.1 |
49.1 |
100.0 |
|
|
Total |
3950 |
100.0 |
100.0 |
||
|
Use of anti-hypertensive medication at baseline exam |
|||||
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
||
|
Valid |
Not currently used |
3771 |
95.5 |
96.8 |
96.8 |
|
Current use |
124 |
3.1 |
3.2 |
100.0 |
|
|
Total |
3895 |
98.6 |
100.0 |
||
|
Missing |
System |
55 |
1.4 |
||
|
Total |
3950 |
100.0 |
|||
|
casual serum at baseline exam |
|||||
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
||
|
Valid |
1 |
3568 |
90.3 |
99.1 |
99.1 |
|
2 |
32 |
.8 |
.9 |
100.0 |
|
|
Total |
3600 |
91.1 |
100.0 |
||
|
Missing |
System |
350 |
8.9 |
||
|
Total |
3950 |
100.0 |
|||
|
Descriptive Statistics |
|||
|
N |
Mean |
Std. Deviation |
|
|
Age at baseline exam (years) |
3950 |
49.95 |
8.644 |
|
Systolic blood pressure at baseline exam (mmHg) |
3950 |
132.838 |
22.3993 |
|
Diastolic blood pressure at baseline exam (mmHg) |
3950 |
83.047 |
12.0522 |
|
Number of cigarettes smoked each day at baseline exam |
3920 |
8.87 |
11.824 |
|
Body Mass Index at baseline exam (kg/m^2) |
3932 |
25.8523 |
4.07827 |
|
Serum total cholesterol at baseline exam (mmg/dL) |
3904 |
237.41 |
44.779 |
|
Casual serum glucose at baseline exam (mg/dL) |
3600 |
82.18 |
24.485 |
|
Valid N (listwise) |
3552 |
||
Q2
|
Case Processing Summary |
|||||||
|
NewVar |
Cases |
||||||
|
Valid |
Missing |
Total |
|||||
|
N |
Percent |
N |
Percent |
N |
Percent |
||
|
Age at baseline exam (years) |
1 |
31 |
96.9% |
1 |
3.1% |
32 |
100.0% |
|
2 |
3556 |
99.7% |
12 |
.3% |
3568 |
100.0% |
|
|
Body Mass Index at baseline exam (kg/m^2) |
1 |
31 |
96.9% |
1 |
3.1% |
32 |
100.0% |
|
2 |
3556 |
99.7% |
12 |
.3% |
3568 |
100.0% |
|
|
Education level * NewVar Crosstabulation |
||||
|
Count |
||||
|
NewVar |
Total |
|||
|
1 |
2 |
|||
|
Education level |
0-11 years |
20 |
1470 |
1490 |
|
High school diploma |
6 |
1020 |
1026 |
|
|
Some college, vocational school |
5 |
572 |
577 |
|
|
College degree or more |
0 |
415 |
415 |
|
|
Total |
31 |
3477 |
3508 |
|
|
Use of anti-hypertensive medication at baseline exam * NewVar Crosstabulation |
||||
|
Count |
||||
|
NewVar |
Total |
|||
|
1 |
2 |
|||
|
Use of anti-hypertensive medication at baseline exam |
Not currently used |
29 |
3402 |
3431 |
|
Current use |
3 |
113 |
116 |
|
|
Total |
32 |
3515 |
3547 |
|
Q3:
|
Case Processing Summary |
|||||||
|
casual serum at baseline exam |
Cases |
||||||
|
Valid |
Missing |
Total |
|||||
|
N |
Percent |
N |
Percent |
N |
Percent |
||
|
Age at baseline exam (years) |
1 |
3556 |
99.7% |
12 |
.3% |
3568 |
100.0% |
|
2 |
31 |
96.9% |
1 |
3.1% |
32 |
100.0% |
|
|
Body Mass Index at baseline exam (kg/m^2) |
1 |
3556 |
99.7% |
12 |
.3% |
3568 |
100.0% |
|
2 |
31 |
96.9% |
1 |
3.1% |
32 |
100.0% |
|
|
Descriptives |
|||||
|
casual serum at baseline exam |
Statistic |
Std. Error |
|||
|
Age at baseline exam (years) |
1 |
Mean |
49.94 |
.145 |
|
|
95% Confidence Interval for Mean |
Lower Bound |
49.66 |
|||
|
Upper Bound |
50.22 |
||||
|
5% Trimmed Mean |
49.82 |
||||
|
Median |
49.00 |
||||
|
Variance |
74.613 |
||||
|
Std. Deviation |
8.638 |
||||
|
Minimum |
32 |
||||
|
Maximum |
70 |
||||
|
Range |
38 |
||||
|
Interquartile Range |
14 |
||||
|
Skewness |
.199 |
.041 |
|||
|
Kurtosis |
-1.014 |
.082 |
|||
|
2 |
Mean |
55.71 |
1.209 |
||
|
95% Confidence Interval for Mean |
Lower Bound |
53.24 |
|||
|
Upper Bound |
58.18 |
||||
|
5% Trimmed Mean |
55.81 |
||||
|
Median |
56.00 |
||||
|
Variance |
45.280 |
||||
|
Std. Deviation |
6.729 |
||||
|
Minimum |
43 |
||||
|
Maximum |
67 |
||||
|
Range |
24 |
||||
|
Interquartile Range |
10 |
||||
|
Skewness |
-.249 |
.421 |
|||
|
Kurtosis |
-.790 |
.821 |
|||
|
Body Mass Index at baseline exam (kg/m^2) |
1 |
Mean |
25.8425 |
.06789 |
|
|
95% Confidence Interval for Mean |
Lower Bound |
25.7094 |
|||
|
Upper Bound |
25.9756 |
||||
|
5% Trimmed Mean |
25.6369 |
||||
|
Median |
25.4250 |
||||
|
Variance |
16.388 |
||||
|
Std. Deviation |
4.04821 |
||||
|
Minimum |
15.54 |
||||
|
Maximum |
56.80 |
||||
|
Range |
41.26 |
||||
|
Interquartile Range |
4.99 |
||||
|
Skewness |
.961 |
.041 |
|||
|
Kurtosis |
2.507 |
.082 |
|||
|
2 |
Mean |
28.3565 |
1.00394 |
||
|
95% Confidence Interval for Mean |
Lower Bound |
26.3061 |
|||
|
Upper Bound |
30.4068 |
||||
|
5% Trimmed Mean |
28.1757 |
||||
|
Median |
28.5000 |
||||
|
Variance |
31.245 |
||||
|
Std. Deviation |
5.58969 |
||||
|
Minimum |
17.17 |
||||
|
Maximum |
43.67 |
||||
|
Range |
26.50 |
||||
|
Interquartile Range |
7.39 |
||||
|
Skewness |
.407 |
.421 |
|||
|
Kurtosis |
.760 |
.821 |
|||
|
Use of anti-hypertensive medication at baseline exam * NewVar Crosstabulation |
||||
|
Count |
||||
|
NewVar |
Total |
|||
|
1 |
2 |
|||
|
Use of anti-hypertensive medication at baseline exam |
Not currently used |
29 |
3402 |
3431 |
|
Current use |
3 |
113 |
116 |
|
|
Total |
32 |
3515 |
3547 |
|
|
Descriptives |
|||||
|
NewVar |
Statistic |
Std. Error |
|||
|
Age at baseline exam (years) |
1 |
Mean |
55.71 |
1.209 |
|
|
95% Confidence Interval for Mean |
Lower Bound |
53.24 |
|||
|
Upper Bound |
58.18 |
||||
|
5% Trimmed Mean |
55.81 |
||||
|
Median |
56.00 |
||||
|
Variance |
45.280 |
||||
|
Std. Deviation |
6.729 |
||||
|
Minimum |
43 |
||||
|
Maximum |
67 |
||||
|
Range |
24 |
||||
|
Interquartile Range |
10 |
||||
|
Skewness |
-.249 |
.421 |
|||
|
Kurtosis |
-.790 |
.821 |
|||
|
2 |
Mean |
49.94 |
.145 |
||
|
95% Confidence Interval for Mean |
Lower Bound |
49.66 |
|||
|
Upper Bound |
50.22 |
||||
|
5% Trimmed Mean |
49.82 |
||||
|
Median |
49.00 |
||||
|
Variance |
74.613 |
||||
|
Std. Deviation |
8.638 |
||||
|
Minimum |
32 |
||||
|
Maximum |
70 |
||||
|
Range |
38 |
||||
|
Interquartile Range |
14 |
||||
|
Skewness |
.199 |
.041 |
|||
|
Kurtosis |
-1.014 |
.082 |
|||
|
Body Mass Index at baseline exam (kg/m^2) |
1 |
Mean |
28.3565 |
1.00394 |
|
|
95% Confidence Interval for Mean |
Lower Bound |
26.3061 |
|||
|
Upper Bound |
30.4068 |
||||
|
5% Trimmed Mean |
28.1757 |
||||
|
Median |
28.5000 |
||||
|
Variance |
31.245 |
||||
|
Std. Deviation |
5.58969 |
||||
|
Minimum |
17.17 |
||||
|
Maximum |
43.67 |
||||
|
Range |
26.50 |
||||
|
Interquartile Range |
7.39 |
||||
|
Skewness |
.407 |
.421 |
|||
|
Kurtosis |
.760 |
.821 |
|||
|
2 |
Mean |
25.8425 |
.06789 |
||
|
95% Confidence Interval for Mean |
Lower Bound |
25.7094 |
|||
|
Upper Bound |
25.9756 |
||||
|
5% Trimmed Mean |
25.6369 |
||||
|
Median |
25.4250 |
||||
|
Variance |
16.388 |
||||
|
Std. Deviation |
4.04821 |
||||
|
Minimum |
15.54 |
||||
|
Maximum |
56.80 |
||||
|
Range |
41.26 |
||||
|
Interquartile Range |
4.99 |
||||
|
Skewness |
.961 |
.041 |
|||
|
Kurtosis |
2.507 |
.082 |
|||
Q4:
DATASET COPY Q4.
DATASET ACTIVATE Q4.
FILTER OFF.
USE ALL.
SELECT IF (NewVar=2).
DATASET ACTIVATE DataSet1.
EXECUTE.
DATASET ACTIVATE Q4.
DATASET ACTIVATE DataSet1.
SAVE OUTFILE='C:UsersRaju ChavanDownloadsassignment stats.sav' /COMPRESSED.
DATASET ACTIVATE Q4.
SAVE OUTFILE='C:UsersRaju ChavanDesktopRR.xlsx' /COMPRESSED.
DATASET ACTIVATE DataSet1.
DATASET ACTIVATE DataSet1.
DATASET CLOSE Q4.
DATASET COPY Q4.
DATASET ACTIVATE Q4.
FILTER OFF.
USE ALL.
SELECT IF (NewVar=2).
DATASET ACTIVATE DataSet1.
EXECUTE.
DATASET ACTIVATE Q4.
RECODE educ (2=1) (ELSE=0) INTO Edu1.
VARIABLE LABELS Edu1 'HighSchoolDiploma'.
EXECUTE.
RECODE educ (3=1) (ELSE=0) INTO Vocation.
VARIABLE LABELS Vocation 'Some College and Vocation'.
EXECUTE.
RECODE SEX (4=1) (ELSE=0) INTO Degree.
VARIABLE LABELS Degree 'College Degree and more'.
EXECUTE.
RECODE BPMEDS.1 (1=1) (ELSE=0) INTO Meditation.
VARIABLE LABELS Meditation 'taken or not'.
EXECUTE.
|
Variables Entered/Removedb |
|||
|
Model |
Variables Entered |
Variables Removed |
Method |
|
1 |
taken or not, HighSchoolDiploma, Body Mass Index at baseline exam (kg/m^2), degree and more, Age at baseline exam (years), Some College and Vocationa |
. |
Enter |
|
a. All requested variables entered. |
|||
|
b. Dependent Variable: Casual serum glucose at baseline exam (mg/dL) |
|||
|
Model Summary |
||||
|
Model |
R |
R Square |
Adjusted R Square |
Std. Error of the Estimate |
|
1 |
.146a |
.021 |
.020 |
14.682 |
|
a. Predictors: (Constant), taken or not, HighSchoolDiploma, Body Mass Index at baseline exam (kg/m^2), degree and more, Age at baseline exam (years), Some College and Vocation |
||||
|
ANOVAb |
||||||
|
Model |
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
|
1 |
Regression |
16607.050 |
6 |
2767.842 |
12.840 |
.000a |
|
Residual |
765023.664 |
3549 |
215.560 |
|||
|
Total |
781630.714 |
3555 |
||||
|
a. Predictors: (Constant), taken or not, HighSchoolDiploma, Body Mass Index at baseline exam (kg/m^2), degree and more, Age at baseline exam (years), Some College and Vocation |
||||||
|
b. Dependent Variable: Casual serum glucose at baseline exam (mg/dL) |
||||||
|
Coefficientsa |
||||||
|
Model |
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
||
|
B |
Std. Error |
Beta |
||||
|
1 |
(Constant) |
63.485 |
2.197 |
28.899 |
.000 |
|
|
Age at baseline exam (years) |
.192 |
.030 |
.112 |
6.471 |
.000 |
|
|
Body Mass Index at baseline exam (kg/m^2) |
.289 |
.062 |
.079 |
4.640 |
.000 |
|
|
HighSchoolDiploma |
-.097 |
.612 |
-.003 |
-.159 |
.873 |
|
|
Some College and Vocation |
-.399 |
.729 |
-.010 |
-.547 |
.584 |
|
|
degree and more |
-.087 |
.822 |
-.002 |
-.106 |
.916 |
|
|
taken or not |
-.772 |
1.423 |
-.009 |
-.542 |
.588 |
|
|
a. Dependent Variable: Casual serum glucose at baseline exam (mg/dL) |
||||||
|
ANOVAb |
||||||
|
Model |
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
|
1 |
Regression |
16477.435 |
2 |
8238.717 |
38.257 |
.000a |
|
Residual |
765153.279 |
3553 |
215.354 |
|||
|
Total |
781630.714 |
3555 |
||||
|
a. Predictors: (Constant), Body Mass Index at baseline exam (kg/m^2), Age at baseline exam (years) |
||||||
|
b. Dependent Variable: Casual serum glucose at baseline exam (mg/dL) |
||||||
|
Coefficientsa |
||||||
|
Model |
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
||
|
B |
Std. Error |
Beta |
||||
|
1 |
(Constant) |
63.350 |
2.009 |
31.526 |
.000 |
|
|
Age at baseline exam (years) |
.192 |
.029 |
.112 |
6.679 |
.000 |
|
|
Body Mass Index at baseline exam (kg/m^2) |
.290 |
.061 |
.079 |
4.727 |
.000 |
|
|
a. Dependent Variable: Casual serum glucose at baseline exam (mg/dL) |
||||||
Q5
|
Paired Samples Statistics |
|||||
|
Mean |
N |
Std. Deviation |
Std. Error Mean |
||
|
Pair 1 |
Casual serum glucose at baseline exam (mg/dL) |
81.04 |
2824 |
20.073 |
.378 |
|
Casual serum glucose at follow-up exam (mg/dL) |
81.83 |
2824 |
22.270 |
.419 |
|
|
Paired Samples Correlations |
||||
|
N |
Correlation |
Sig. |
||
|
Pair 1 |
Casual serum glucose at baseline exam (mg/dL) & Casual serum glucose at follow-up exam (mg/dL) |
2824 |
.438 |
.000 |
|
Paired Samples Test |
|||||||||
|
Paired Differences |
t |
df |
Sig. (2-tailed) |
||||||
|
Mean |
Std. Deviation |
Std. Error Mean |
95% Confidence Interval of the Difference |
||||||
|
Lower |
Upper |
||||||||
|
Pair 1 |
Casual serum glucose at baseline exam (mg/dL) - Casual serum glucose at follow-up exam (mg/dL) |
-.785 |
22.513 |
.424 |
-1.616 |
.045 |
-1.854 |
2823 |
.064 |
For Group 1:
|
Paired Samples Statistics |
|||||
|
Mean |
N |
Std. Deviation |
Std. Error Mean |
||
|
Pair 1 |
Casual serum glucose at baseline exam (mg/dL) |
271.36 |
14 |
69.373 |
18.541 |
|
Casual serum glucose at follow-up exam (mg/dL) |
211.00 |
14 |
64.709 |
17.294 |
|
|
Paired Samples Correlations |
||||
|
N |
Correlation |
Sig. |
||
|
Pair 1 |
Casual serum glucose at baseline exam (mg/dL) & Casual serum glucose at follow-up exam (mg/dL) |
14 |
.420 |
.135 |
|
Paired Samples Test |
|||||||||
|
Paired Differences |
t |
df |
Sig. (2-tailed) |
||||||
|
Mean |
Std. Deviation |
Std. Error Mean |
95% Confidence Interval of the Difference |
||||||
|
Lower |
Upper |
||||||||
|
Pair 1 |
Casual serum glucose at baseline exam (mg/dL) - Casual serum glucose at follow-up exam (mg/dL) |
60.357 |
72.298 |
19.322 |
18.613 |
102.101 |
3.124 |
13 |
.008 |
For Group 2:
|
Paired Samples Statistics |
|||||
|
Mean |
N |
Std. Deviation |
Std. Error Mean |
||
|
Pair 1 |
Casual serum glucose at baseline exam (mg/dL) |
80.10 |
2810 |
14.186 |
.268 |
|
Casual serum glucose at follow-up exam (mg/dL) |
81.19 |
2810 |
19.887 |
.375 |
|
|
Paired Samples Correlations |
||||
|
N |
Correlation |
Sig. |
||
|
Pair 1 |
Casual serum glucose at baseline exam (mg/dL) & Casual serum glucose at follow-up exam (mg/dL) |
2810 |
.231 |
.000 |
|
Paired Samples Test |
|||||||||
|
Paired Differences |
t |
df |
Sig. (2-tailed) |
||||||
|
Mean |
Std. Deviation |
Std. Error Mean |
95% Confidence Interval of the Difference |
||||||
|
Lower |
Upper |
||||||||
|
Pair 1 |
Casual serum glucose at baseline exam (mg/dL) - Casual serum glucose at follow-up exam (mg/dL) |
-1.090 |
21.598 |
.407 |
-1.889 |
-.291 |
-2.675 |
2809 |
.008 |
References:
Abbott, M. L. (2016). Using Statistics in the Social and Health Sciences with SPSS and Excel. John Wiley & Sons.
Bickel, P. J., & Doksum, K. A. (2015). Mathematical statistics: basic ideas and selected topics, volume I (Vol. 117). CRC Press.
Chatterjee, S., & Hadi, A. S. (2015). Regression analysis by example. John Wiley & Sons.
Darlington, R. B., & Hayes, A. F. (2016). Regression analysis and linear models: Concepts, applications, and implementation. Guilford Publications.
Draper, N. R., & Smith, H. (2014). Applied regression analysis (Vol. 326). John Wiley & Sons.
Fox, J. (2015). Applied regression analysis and generalized linear models. Sage Publications.
Glantz, S. A., Slinker, B. K., & Neilands, T. B. (2016). Primer of applied regression & analysis of variance. McGraw-Hill Medical Publishing Division.
Larson-Hall, J. (2015). A guide to doing statistics in second language research using SPSS and R. Routledge.
Pett, M. A. (2015). Nonparametric statistics for health care research: Statistics for small samples and unusual distributions. Sage Publications.
Pett, M. A. (2015). Nonparametric statistics for health care research: Statistics for small samples and unusual distributions. Sage Publications.
Rasch, D., & Schott, D. (2018). Basic Ideas of Mathematical Statistics. Mathematical Statistics, 1-38.
Schroeder, L. D., Sjoquist, D. L., & Stephan, P. E. (2016). Understanding regression analysis: An introductory guide (Vol. 57). Sage Publications.
Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics. Allyn & Bacon/Pearson Education.
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