plot.OpenStatsMM | R Documentation |
This function visualises an 'OpenStatsMM' object
## S3 method for class 'OpenStatsMM' plot(x, main = "Final Model", ask = FALSE, mfrow = c(2, 2), ...)
x |
an instance of ‘OpenStatsMM' result from OpenStatsAnalysis(method = ’MM') function |
main |
a string to be pasted to the title of the plots |
ask |
see 'ask' in 'par()' function. Default FALSE |
mfrow |
the screen partition. see 'mfrow' argument in the 'par' function. Default c(2,2) then all plots display in one screen. |
... |
other parameters that can be passed to the 'plot' function |
The plot function creates some visualisations for the linear mixed model framework:
- Residual versus fitted values
- Residual density plot and the normality test p-value
- Residual Q-Q plot
- The density plot of the response variable and the normality test p-value
Not applicable
Hamed Haseli Mashhadi <hamedhm@ebi.ac.uk>
OpenStatsAnalysis
, plot.OpenStatsFE
, plot.OpenStatsRR
#################################################################### # Data preparation #################################################################### ################# # Continuous data - Creating OpenStatsList object ################# fileCon <- system.file("extdata", "test_continuous.csv", package = "OpenStats") test_Cont <- OpenStatsList( dataset = read.csv(fileCon), testGenotype = "experimental", refGenotype = "control", dataset.colname.genotype = "biological_sample_group", dataset.colname.batch = "date_of_experiment", dataset.colname.lifestage = NULL, dataset.colname.weight = "weight", dataset.colname.sex = "sex" ) ################# # Optimised Linear Mixed model (MM) framework ################# MM1_result <- OpenStatsAnalysis( OpenStatsList = test_Cont, method = "MM", MM_fixed = data_point ~ Genotype + Weight ) print(MM1_result, col = 2, main = "Optimised model")
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