R: Oneway Repeated Analysis of variance (ANOVA)

hanaml.OnewayAnovaRepeated {hana.ml.r}

R Documentation

Oneway Repeated Analysis of variance (ANOVA)

Description

Performs one-way repeated measures analysis of variance, along with Mauchly's Test of Sphericity and post hoc multiple comparison tests.

Usage

hanaml.OnewayAnovaRepeated(conn.context,
                           data,
                           subject.id = NULL,
                           measures = NULL,
                           multcomp.method = NULL,
                           significance.level = NULL,
                           se.type = NULL)

Arguments

`conn.context`	`ConnectionContext` Connection to SAP HANA System
`data`	`DataFrame` DataFrame containing the data.
`subject.id`	`character, optional` Name of the subject ID column.. The algorithm treats each row of the data table as a different subject. Hence there should be no duplicate subject ids in this column. If not provided, it defaults to the first columns.
`measures`	`character, optional` Names of the groups (measures). If not provided, defaults to all non subject.id columns.
`multcomp.method`	`character, optional` Method used to perform multiple comparison tests. #' `"tukey-kramer"` `"bonferroni"` `"dunn-sidak"` `"scheffe"` `"fisher-lsd"` Defaults to 'bonferroni'
`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.
`se.type`	`character, optional` Type of standard error used in multiple comparison tests. `all-data`: computes the standard error from all data. It has more power if the assumption of sphericity is TRUE, especially with small data sets. `two-group`: computes the standard error from only the two groups being compared. It doesn't assume sphericity. Defaults to 'two-group'.

Value

Statistics for each group: DataFrame
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.
Mauchly test results, DataFrame
structured as follows:
- STAT_NAME, type NVARCHAR(100), names of test result quantities.
- STAT_VALUE, type DOUBLE, values of test result quantities.
Computed results for ANOVA : DataFrame
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. - P_VALUE_GG, type DOUBLE, p-value of Greehouse-Geisser correction. - P_VALUE_HF, type DOUBLE, p-value of Huynh-Feldt correction. - P_VALUE_LB, type DOUBLE, p-value of lower bound correction.
Multiple comparison results: DataFrame
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.

Examples

## Not run: 
Input DataFrame data:
> data$collect()
    ID  MEASURE1  MEASURE2  MEASURE3  MEASURE4
  0  1       8.0       7.0       1.0       6.0
  1  2       9.0       5.0       2.0       5.0
  2  3       6.0       2.0       3.0       8.0
  3  4       5.0       3.0       1.0       9.0
  4  5       8.0       4.0       5.0       8.0
  5  6       7.0       5.0       6.0       7.0
  6  7      10.0       2.0       7.0       2.0
  7  8      12.0       6.0       8.0       1.0
 Call the function:
 > result <- hanaml.OnewayAnovaRepeated(conn,
                                        data,
                                        multcomp.method = "bonferroni",
                                        significance.level = 0.05,
                                        se.type = "two-group")
 Expected output:
 > result[[1]]
         GROUP    VALid_SAMPLES    MEAN        SD
   0  MEASURE1              8     8.125  2.232071
   1  MEASURE2              8     4.250  1.832251
   2  MEASURE3              8     4.125  2.748376
   3  MEASURE4              8     5.750  2.915476

## End(Not run)

[Package hana.ml.r version 1.0.8 Index]

Oneway Repeated Analysis of variance (ANOVA)

Description

Usage

Arguments

Value

See Also

Examples