Description Usage Arguments Value Examples

View source: R/compute_scores.R

Computes QC-ART scores

1 | ```
qcart(all_data, baseline, variables, prop = 0.95)
``` |

`all_data` |
a data frame of all of the data to be analyzed |

`baseline` |
vector identifying which rows of 'all_data' are the baseline observations |

`variables` |
vector of numbers or column names identifying which columns are the variables to use to compute scores |

`prop` |
how many latent variables should be retained? proportion of variability explianed by the latent variables |

vector of QC-ART scores corresponding to the rows of 'all_data'

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | ```
library(lubridate)
library(QCART)
library(dplyr)
library(ggplot2)
#Load the Amidan et al. (2014) dataset
data("amidan_et_al")
#Use `lubridate` to make wokring with time stamps easier
amidan$Acq_Time_Start <- mdy_hm(amidan$Acq_Time_Start)
#Choose one particular instrument to analyze and arrange the rows by time
chosen_inst <- "VOrbiETD04"
vorb_04 <- filter(amidan,Instrument==chosen_inst)
vorb_04 <- arrange(vorb_04,Acq_Time_Start)
#Remove the first 6 rows that occured prior to an instrument cleaning
vorb_04 <- vorb_04[-c(1:6),]
#Choose the variables that will be used to compute QC-ART scores
chosen_vars <- c("P_2C","MS1_Count","MS2_Count","MS1_2B","MS2_1","MS2_2","MS2_3","MS2_4A","MS2_4B","RT_MS_Q1","RT_MS_Q4","RT_MSMS_Q1","RT_MSMS_Q4","XIC_WideFrac")
#Define which observations will be used as the baseline
bline_ob <- 1:50
vorb_04$Baseline <- FALSE
vorb_04$Baseline[bline_ob] <- TRUE
#Compute the scores for that instrument, baseline set and variables
vorb_04$QC_Art <- qcart(all_data = vorb_04, baseline = bline_ob, variables = chosen_vars)
#Plot the scores over time
qplot(Acq_Time_Start,QC_Art,data=vorb_04,colour=Baseline)+xlab("Date")+ylab("QC-ART Score")
``` |

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