One-way Analysis of variance (ANOVA)

hanaml.OnewayAnova is a R wrapper for SAP HANA PAL ANOVA.

hanaml.OnewayAnova(
  data,
  group = NULL,
  sample = NULL,
  multcomp.method = NULL,
  significance.level = NULL
)

Arguments

data

DataFrame
DataFrame containting the data.
group

character, optional
Name of the group column.
If not provided, it defaults to the first column of data.
sample

character, optional
Name of the sample measurement column.
If not provided, it defaults to the second column of data
multcomp.method

character, optional

  • "tukey-kramer"

  • "bonferroni"

  • "dunn-sidak"

  • "scheffe"

  • "fisher-lsd"

Defaults to 'tukey-kramer'.
significance.level

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.

Value

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.

Details

The purpose of one-way ANOVA is to determine whether there is any statistically significant difference between the means of three more independent groups.

Examples

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

See also

hanaml.OnewayAnovaRepeated