hanaml.OnewayAnova.Rd
hanaml.OnewayAnova is a R wrapper for SAP HANA PAL ANOVA.
hanaml.OnewayAnova(
data,
group = NULL,
sample = NULL,
multcomp.method = NULL,
significance.level = NULL
)
DataFrame
DataFrame containting the data.
character, optional
Name of the group column.
If not provided, it defaults to the first column of data.
character, optional
Name of the sample measurement column.
If not provided, it defaults to the second column of data
character, optional
"tukey-kramer"
"bonferroni"
"dunn-sidak"
"scheffe"
"fisher-lsd"
Defaults to 'tukey-kramer'.
double, optional
The significance level when the function calculates the confidence
interval in multiple comparison tests.
Values must be greater than 0 and less than 1.
Defaults to 0.05.
Returns a list of 3 DataFrame:
DataFrame 1
Statistics for each group, structured as follows:
GROUP, type NVARCHAR(256), group name.
VALID_SAMPLES, type INTEGER, number of valid samples.
MEAN, type DOUBLE, group mean.
SD, type DOUBLE, group standard deviation.
DataFrame 2
Computed results for ANOVA, structured as follows:
VARIABILITY_SOURCE, type NVARCHAR(100), source of variability, including between groups, within groups (error) and total.
SUM_OF_SQUARES, type DOUBLE, sum of squares.
DEGREES_OF_FREEDOM, type DOUBLE, degrees of freedom.
MEAN_SQUARES, type DOUBLE, mean squares.
F_RATIO, type DOUBLE, calculated as mean square between groups divided by mean square of error.
P_VALUE, type DOUBLE, associated p-value from the F-distribution.
DataFrame 3
Multiple comparison results, structured as follows:
FIRST_GROUP, type NVARCHAR(256), the name of the first group to conduct pairwise test on.
SECOND_GROUP, type NVARCHAR(256), the name of the second group to conduct pairwise test on.
MEAN_DIFFERENCE, type DOUBLE, mean difference between the two groups.
SE, type DOUBLE, standard error computed from all data.
P_VALUE, type DOUBLE, p-value.
CI_LOWER, type DOUBLE, the lower limit of the confidence interval.
CI_UPPER, type DOUBLE, the upper limit of the confidence interval.
The purpose of one-way ANOVA is to determine whether there is any statistically significant difference between the means of three more independent groups.
Input DataFrame data:
> data$Collect()
GROUP DATA
1 A 4.0
2 A 5.0
3 A 4.0
4 A 3.0
5 A 2.0
...
20 C 6.0
21 C 7.0
22 C 5.0
Call the function:
> result <- hanaml.OnewayAnova(data,
multcomp.method = "tukey-kramer",
significance.level = 0.05)
Expected output:
> result[[1]]
GROUP VALID_SAMPLES MEAN SD
1 A 8 3.625000 0.916125
2 B 8 5.750000 1.581139
3 C 6 6.166667 0.752773
4 Total 22 5.090909 1.600866