Description
Presentation of the Results and Findings Section
Interpret The Statistical Analysis
Unformatted Attachment Preview
Purchase answer to see full attachment
Explanation & Answer
Please find attached
Running Head: INTERPRETING SPSS OUTPUT
Interpreting SPSS Output
Name
Institution
1
INTERPRETING SPSS OUTPUT
2
Descriptive Statistics and Frequency Output
From the descriptive statistics output, it is apparent that a total of 804 hospitals were
considered for analysis. Of these, 711 were 340B hospitals and 93 hospitals were of other types.
From this table, it is apparent that there is a variation in the means for the different infections
recorded in the different hospitals. Further analysis was necessary to determine whether the
differences in means were statistically significant. For instance, CAUTI W had the highest mean
while MRSA W had the lowest mean. There were also differences in the standard deviations for
the different infections (CLABSI W, CAUTI W, and MRSA W). However, further analysis was
required to establish whether there was a significant variation in the variances for the different
infection types. In terms of range, CAUTI W had the smallest minimum value while MRSA W
had the largest maximum value. None of the variables had a missing value. In terms of skewness,
340B Hospitals had a skewness of -2.408 which is outside the range of -1 to +1. As such, the
data for 340B hospitals is left skewed and hence fails to meet the normality requirement.
Additionally, the kurtosis value of the 340B Hospital data is 3.807 which is far much larger than
+1.0. This high value indicates that the data is leptokurtic, further confirming that the 340B
hospital data is not normally distributed. For OwnerCat, the skewness value is 0.025 and hence
very close to zero. The kurtosis value is also -0.185 which is within the normal range. As such,
the distribution of the OwnerCat data is normal.
The frequency table also shows the distribution of the 340B Hospitals and the OwnerCat
hospitals. 340B hospitals are divided into two categories – other and 340B. The ‘other’ category
consists of 93 hospitals while the ‘340B’ category consists of 711 hospitals; making a total of
804 hospitals. In terms of ownership (OwnerCat), the hospitals are categorizes into government
INTERPRETING SPSS OUTPUT
3
(189), nonprofit (517) and AllOther (98); making a total of 804. None of these categories
(variables) had a missing value.
Tests of Homogeneity of Variances, df1=1
In testing the homogeneity of variances, it is apparent from the SPSS output that all the
significance values for the three infection types – CLABSI W, CAUTI W and MRASA W –
based on mean; median; median and with adjusted df; and based on trimmed mean are all greater
than 0.05. CLABSI W (based on mean (1,635), p=0.964; based on median (1, 635), p=0.957;
based on median and with adjusted df (1, 634.927), p=0.957; based on trimmed mean (1, 635),
p=0.973), CAUTI W (based on mean (1,706), p=0.067; based on median (1, 706), p=0.077;
based on median and with adjusted df (1, 701.979), p=0.077; based on trimmed mean (1, 706),
p=0.069), MRSA W (based on mean (1,601), p=0.075; based on median (1, 601), p=0.101; based
on median and with adjusted df (1, 598.006), p=0.101; based on trimmed mean (1, 601),
p=0.079), TOTAL HAC (based on mean (1,802), p=0.893; based on median (1, 802), p=0.887;
based on median and with adjusted df (1, 798.308), p=0.887; based on trimmed mean (1, 802),
p=0.894). Since the significance values are greater than 0.05, Levene’s Test is non-significant
and the variances are not statistically significant different. As such, equal variances are assumed
for the ANOVA test.
ANOVA, df=1
For CLABSI W, the significance value is 0.390 which is greater than the alpha value of
0.05. As such, the differences in means between and within groups are not statistically
significantly different. For CAUTI W, the significance value is 0.505 which is greater than the
alpha value of 0.05. Consequently, the differences in means between and within groups are not
statistically significantly different. Also, for MRSA W, the significance value is 0.525 which is
INTERPRETING SPSS OUTPUT
4
greater than 0.05. As such, the differences in means between and within groups are not
statistically significantly different. However, for the TOTAL HAC, the significance is 0.018
which is less than 0.05. This means that the differences in means between and within groups are
statistically significantly different.
ANOVA Effect Sizes, df=1
The significance values from the ANOVA output only indicate whether differences
between and within groups are statistically significant. However, these significance values do not
indicate how important the differences are. As such, an ANOVA effect size analysis was
conducted to determine the importance of the differences in means between and within groups.
For CLABSI W the point estimate value of the eta-squared is 0.001, for CAUTI W the point
estimate is 0.001, for MRSA W the point estimate is 0.001 and for TOTAL HAC the point
estimate is 0.007. Therefore, for all the infection types, the effect sizes of the differences are less
than 1%. Since the effect sizes are so low, they are not significant and hence lack any practical
significance. Therefore, though there are statistically significance differences in means between
and within groups for TOTAL HAC, the differences are very small to the extent that they lack
any practical significance.
Tests of Homogeneity of Variances, df1=2
When the degrees of freedom were changed so that df1=2, the values for significance for
CLABSI W were all greater than 0.05 (Based on mean = 0.626, based on median = 0.711, based
on median and with adjusted df = 0.711, and based on trimmed mean = 0.661). Therefore,
Levene’s Test is non-significant and the variances are not statistically significantly different. As
such, equal variances are assumed for the ANOVA test.
INTERPRETING SPSS OUTPUT
5
For CAUTI W, the significance values were all less than 0.05 (Based on mean = 0.006,
based on median = 0.009, based on median and with adjusted df = 0.009, and based on trimmed
mean = 0.007). Consequently, Levene’s Test is significant and the variances are statistically
significantly different. As such, unequal variances are assumed for the ANOVA test.
For MRSA W, the significance values are all greater than 0.05 (Based on mean = 0.378,
based on median = 0.460, based on median and with adjusted df = 0.460, and based on trimmed
mean = 0.398). Therefore, Levene’s Test is non-significant and the variances are not statistically
significantly different. As such, equal variances are assumed for the ANOVA test.
For TOTAL HAC, the significance values were also all greater than 0.05 (Based on mean
= 0.276, based on median = 0.275, based on median and with adjusted df = 0.275, and based on
trimmed mean = 0.273). Therefore, Levene’s Test is non-significant and the variances are not
statistically significantly different. As such, equal variances are assumed for the ANOVA test.
ANOVA, df=2
For CLABSI W, the significance value is 0.299 which is greater than the alpha value of
0.05. As such, the differences in means between and within groups are not statistically
significantly different. For CAUTI W, the significance value is 0.753 which is greater than the
alpha value of 0.05. Consequently, the differences in means between and within groups are not
statistically significantly different. Also, for MRSA W, the significance value is 0.602 which is
greater than 0.05. As such, the differences in means between and within groups are not
statistically significantly different. For the TOTAL HAC, the significance is 0.796 which is
greater than 0.05. As such, the differences in means between and within groups are not
statistically significantly different.
ANOVA Effect Sizes, df=2
INTERPRETING SPSS OUTPUT
6
For CLABSI W the point estimate value of the eta-squared is 0.004, for CAUTI W the
point estimate is 0.001, for MRSA W the point estimate is 0.002 and for TOTAL HAC the point
estimate is 0.001. Therefore, for all the infection types, the effect sizes of the differences are less
than 1%. Since the effect sizes are so low, they are not significant and hence lack any practical
significance. In other words, the differences are very small to the extent that they lack any
practical significance.
Post Hoc Tests
To test how the distributions of the different infections types compare among
government, nonprofit and AllOther hospital categories, Tukey post hoc tests were conducted.
For CLA BSI W, the significance value was 1.0 when the distributions were compared between
government and nonprofit as well as between government and AllOther. Since the significance
value was much greater than 0.05, then there were no statistically significant distribution of
CLABSI W between government hospitals and nonprofit hospitals as well as between
government hospitals and AllOther hospitals. On the other hand, there is a slight difference in the
distribution of CLABSI W between nonprofit and AllOther hospitals. However, with a
significance value of 0.418, the difference is statistically insignificant.
For CAUTI W, there is no statistical difference in its distribution among all the three
hospital types since a significance value of 1.0 (which is much greater than 0.05) was reported
for all the three comparisons. For MRSA W, there was a slight difference in its distribution
between government hospitals and nonprofit hospitals. However, with a significance value of
0.944 (which is much greater than 0.05), the difference is not statistically significant. On the
other hand, the significance value for the distribution between government and AllOther as well
as between nonprofit and AllOther was 1.0. Since 1.0 is much greater than 0.05, the difference in
INTERPRETING SPSS OUTPUT
7
these comparisons were statistically insignificant. Lastly, all comparisons for the TOTAL HAC
had a significance value of 1.0. Since 1.0 is much greater than 0.05, then there was no
statistically significant difference in distribution.
Nonparametric Tests
To test the distribution of the infections types across the categories of the two groups of
hospitals – 340B HOSPITALS and OwnerCat – the independent samples Mann-Whitney U Test
and the independent samples Kruskal-Wallis Test were conducted. For the CLABSI W, the null
hypothesis was that the distribution of CLABSI W Z SCORE is the same across categories of
340B HOSPITALS. From the independent samples Mann-Whitney U Test, the significance
value was 0.51. Since 0.51 is much greater than 0.05, there was no statistically significant
difference in distribution. As such, the null hypothesis was retained. It was, therefore, concluded
that the distribution of CLABSI W Z SCORE is the same across categories of 340B
HOSPITALS. For the OwnerCat hospitals, the null hypothesis was that the distribution of
CLABSI W Z SCORE is the same across categories of OwnerCat. The results of the independent
samples Kruskal-Wallis Test gave a significance value of 0.416. Since 0.416 is much greater
than 0.05, there were no statistically significant differences in distribution. As such, the null
hypothesis was retained. It was, therefore, concluded that the distribution of CLABSI W Z
SCORE is the same across categories of OwnerCat.
For the CAUTI W, the null hypothesis was that the distribution of CAUTI W Z SCORE
is the same across categories of 340B HOSPITALS. From the independent samples MannWhitney U Test, the significance value was 0.423. Since 0.423 is much greater than 0.05, there
was no statistically significant difference in distribution. As such, the null hypothesis was
retained. It was, therefore, concluded that the distribution of CAUTI W Z SCORE is the same
INTERPRETING SPSS OUTPUT
8
across categories of 340B HOSPITALS. For the OwnerCat hospitals, the null hypothesis was
that the distribution of CAUTI W Z SCORE is the same across categories of OwnerCat. The
results of the independent samples Kruskal-Wallis Test gave a significance value of 0.978. Since
0.978 is much greater than 0.05, there were no statistically significant differences in distribution.
As such, the null hypothesis was retained. It was, therefore, concluded that the distribution of
CAUTI W Z SCORE is the same across categories of OwnerCat.
For the MRSA W, the null hypothesis was that the distribution of MRSA W Z SCORE is
the same across categories of 340B HOSPITALS. From the independent samples Mann-Whitney
U Test, the significance value was 0.244. Since 0.244 is greater than 0.05, there was no
statistically significant difference in distribution. As such, the null hypothesis was retained. It
was, therefore, concluded that the distribution of MRSA W Z SCORE is the same across
categories of 340B HOSPITALS. For the OwnerCat hospitals, the null hypothesis was that the
distribution of MRSA W Z SCORE is the same across categories of OwnerCat. The results of the
independent samples Kruskal-Wallis Test gave a significance value of 0.458. Since 0.458 is
much greater than 0.05, there were no statistically significant differences in distribution. As such,
the null hypothesis was retained. It was, therefore, concluded that the distribution of MRSA W Z
SCORE is the same across categories of OwnerCat.
For the TOTAL HAC, the null hypothesis was that the distribution of TOTAL HAC
SCORE is the same across categories of 340B HOSPITALS. From the independent samples
Mann-Whitney U Test, the significance value was 0.020. Since 0.020 is much smaller than 0.05,
there was a statistically significant difference in distribution. As such, the null hypothesis was
rejected. It was, therefore, concluded that the distribution of TOTAL HAC SCORE is not the
same across categories of 340B HOSPITALS. For the OwnerCat hospitals, the null hypothesis
INTERPRETING SPSS OUTPUT
9
was that the distribution of TOTAL HAC SCORE is the same across categories of OwnerCat.
The results of the independent samples Kruskal-Wallis Test gave a significance value of 0.861.
Since 0.861 is much greater than 0.05, there were no st...
Review
Review
