ttest | R Documentation |
A t-test compares the means of two factor levels. Multiple-test corrected p-values are used to indicate the significance of the computed difference for all features.
ttest(
alpha = 0.05,
mtc = "fdr",
factor_names,
paired = FALSE,
paired_factor = character(0),
equal_variance = FALSE,
conf_level = 0.95,
control_group = NULL,
...
)
alpha |
(numeric) The p-value cutoff for determining significance. The default is |
mtc |
(character) Multiple test correction method. Allowed values are limited to the following:
The default is |
factor_names |
(character) The name of sample meta column(s) to use. |
paired |
(logical) Apply a paired t-test. The default is |
paired_factor |
(character) The factor name that encodes the sample id for pairing. The default is |
equal_variance |
(logical) Equal variance. Allowed values are limited to the following:
The default is |
conf_level |
(numeric) The confidence level of the interval. The default is |
control_group |
(character, NULL) The level name of the group used as the second group (where possible) when computing t-statistics. This ensures a positive t-statistic corresponds to an increase when compared to the control group. The default is |
... |
Additional slots and values passed to |
A ttest
object with the following output
slots:
t_statistic | (data.frame) The value of the calculate statistics which is converted to a p-value when compared to a t-distribution. |
p_value | (data.frame) The probability of observing the calculated t-statistic. |
dof | (numeric) The number of degrees of freedom used to calculate the test statistic. |
significant | (data.frame) TRUE if the calculated p-value is less than the supplied threhold (alpha). |
conf_int | (data.frame) Confidence interval for t statistic. |
estimates | (data.frame) The group means estimated when computing the t-statistic. |
A ttest
object inherits the following struct
classes:
[ttest]
>> [model]
>> [struct_class]
M = ttest(
alpha = 0.05,
mtc = "fdr",
factor_names = "V1",
paired = FALSE,
paired_factor = "NA",
equal_variance = FALSE,
conf_level = 0.95,
control_group = NULL)
M = ttest(factor_name='Class')
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