diff options
Diffstat (limited to 'admin/survey/modules/mod_kakovost')
| -rw-r--r-- | admin/survey/modules/mod_kakovost/R/kakovost.R | 376 | ||||
| -rw-r--r-- | admin/survey/modules/mod_kakovost/class.SurveyKakovost.php | 12 |
2 files changed, 348 insertions, 40 deletions
diff --git a/admin/survey/modules/mod_kakovost/R/kakovost.R b/admin/survey/modules/mod_kakovost/R/kakovost.R index de05f1e..d7fa8d0 100644 --- a/admin/survey/modules/mod_kakovost/R/kakovost.R +++ b/admin/survey/modules/mod_kakovost/R/kakovost.R @@ -1,47 +1,357 @@ -#uporabnost <- function(params){
+# Created by Miha 27.5.2021
+# Modified (sixth version) by Miha 7.6.2021
-#setwd("path od mape, kjer se nahaja ta glavna datoteka, npr. C:/mapa")
-# Import data.table & functions ------------------------------------------------------
-require("data.table")
-source("modules/mod_uporabnost/R/gen.survey.str.R")
-source("modules/mod_uporabnost/R/gen.usability.matrix.R")
-source("modules/mod_uporabnost/R/calc.usability.R")
+# Note: The formated banners of comments are generated with
+#' @bannerCommenter package.
-# Input data ------------------------------------------------------
+
+###########################################################################
+###########################################################################
+### ###
+### DESCRIPTION: ###
+### RESPONSE TIME WINSORIZATION ###
+### ###
+###########################################################################
+###########################################################################
+#' @param VVMM PRIPRAVA PODATKOV:
+#' NOTE: tole kodo smo po VV zmišljevanjui tolikokrat spremenili
+#' da se mi ne da več pisat v angleščini in konstantno popravljati :)
+#'
+# Za ustrezno obravnavo časov, je treba predhodno pripraviti podatke.
+# Glavni problemi ki pri tem nastanejo so: respondenti, ki na določeni strani
+# niso odogovrili na vsa vprašanja zaradi česar so njihovi časi neupraviečno
+# prekratki,potem nerespondenti, ki so priskočili določeno stran 3) respodneti,
+# ki so na določeni strnai imeli notranji pogodj oz so izbrali vprašanje drugo.
+# In 4) respondeti, ki so prepočasni v smislu gausov eksponentre krivulje kar
+# se vstorki obravnava z postopki in odstraniujo asimetrijo v normalbi porazdleitvi
+# zaradi aktere pride do amanomalj vtestirnaju 5) popravek za čase respondentov,
+# ki so prekinili izpolnjevanje
+
+# Postopek metode
+
+#' @1.Trunciranje enote, ki so na posamezni strani nad 95tim percentilom
+#' @2.Strani, ki so nagovori se pri izračunu indeksa ne upošteva
+#' @3.Preverimo ali je stran za respondenta mešana, torej ali vprašanja
+#' oziroma postavke, poleg veljavnih vrednosti respondenta na stran
+#' (verdnosti večje od 1), vsebujejo še kakšno manjkajočo vrednost zaradi pogoja
+#' (-2)
+#' @4.V kolikor obstajajo mešane vrednosti, potem čas respondenta na tej mešani
+#' strani pomnožimo z deležem ocenjenega časa, ki bi na tej strnai sicer
+#' pripadal temu vprašanju. Privzeta tehnična meritev orodja za spletno anketirnaje,
+#' ki ima algoritem( priloži sliko 1KA časov). Zmanjšaš čas, za 10 procentov
+#' (pomnožiš z 90 %).
+#' @5.Preverimo ali so na strani respondenta manjkajoče vrednosti. Če manjkajoča
+#' vrednost obstaja, čas respondenta na tej strani delimo z 0.9
+#' @6.Nato izračunamo indeks respondenta (Rti), ki je izračunan tako, da vsot
+#' o strani respondenta (brez -2) delimo z vsoto median taistih strani.
+#' @7. Ponovno izračunamo mediane strani.
+#' @8. Vrednosti, ki smo jih v prvem koraku truncirali imputiramo, in sicer so
+#' truncirane vrednosti zmnožek indeksa posameznega respondenta pomnožene z mediano
+#' strani oziroma Rti * mediana stranii
+
+#------------------------- // DESCRIPTION // -----------------------------#
+
+
+#------------ List of packages we need --------------#
+library(data.table)
+library(dplyr)
+#------------ List of packages we need --------------#
+
+
+
+############################################################################
+############################################################################
+### ###
+### DATA: ###
+### IMPORT AMD PREPARATION ###
+### ###
+############################################################################
+############################################################################
+
+#setwd("E:\\Doktorat\\Modul kakovost 1ka/")
+
+##---------------------
+## Input on 1KA side
+##---------------------
+# To know for which survey we are calculating response time
params <- commandArgs(trailingOnly = TRUE)
ID <- params[1]
+#ID <- 8699
+
+##----------------------------
+## Import data and paradata
+##----------------------------
+# We need thrtee files
+#' @data: data frame with paradata (response time)
+#' @questions: data about page ID nad number of
+#' items/variables per page, in order to properly calculate our
+#' index
+#' @items: questions item info. Important part is char_count, which
+#' represents the 1KA estimeted time (100 char_count == 10 sekund)
+#' We will merge items and questions
+
+
+
+## Data -----
+# path
+rt.file <- paste0("modules/mod_kakovost/temp/data_", ID, ".csv")
+# Import
+rt <-
+ as.data.frame(fread(rt.file, header = TRUE), stringsAsFactors = FALSE)
+
+## Questionns --------
+# get question and item files
+questions.file <-
+ paste0("modules/mod_kakovost/temp/questions_", ID, ".csv")
+# Import
+questions <-
+ fread(
+ questions.file,
+ header = TRUE,
+ data.table = FALSE
+ )
+# Check if there is question type "Nagovor", we want to omit
+# this form analysis
+
+# FOR NOW: later we will retunr back
+# more testing is needed
+questions$params <-
+ ifelse(grepl("nagovor", questions$params), questions$params, "")
+
+
+## Items --------
+# We need ITems to calculate response time pe ritem
+# and use it in calculation of response time
+## Questionns --------
+# get question and item files
+items.file <-
+ paste0("modules/mod_kakovost/temp/items_", ID, ".csv")
+# Import
+items <-
+ fread(
+ items.file,
+ header = TRUE,
+ data.table = FALSE
+ )
+
+
+
+
+# Important
+# 1KA računa čas na naslednji način
+# Čas za vprašanje (na 100 znakov besedila) = 10 sekund
+# Čas za kategorijo (na 100 znakov besedila) = 5 sekund
+# Torej bomo znake pretvorili v sekunde
+
+# Vprašanje
+questions$cas1KA <- questions$char_count * 10 / 100
+# Kategorija
+items$cas1KA <- items$char_count * 5 / 100
+
+
+# Merge Questions and items in order to get number of character per
+# item and per questions
+Ques.item <-
+ merge(questions,
+ items,
+ by = "ID QUESTION",
+ all = TRUE,
+ sort = FALSE)
+
+# Sort from smallest to largest, so the first page is always
+# in the beginning
+Ques.item <- arrange(Ques.item, `ID PAGE`)
+
+
+#--------------------------------------------------------------------------#
+
+
+############################################################################
+############################################################################
+### ###
+### RESPONSE TIME ###
+### CALCULATE RESPONSE TIME IN SECONDS FOR EACH PAGE ###
+### ###
+############################################################################
+############################################################################
+## SUBSET COLNAMES "date_" ##
+# Iz baze izberemo le stolpce, ki nas zanimajo:
+# Vse stolpce, ki v imenu vsebujejo Date_ (ker ra?unamo ?ase na strani)
+times <- rt[, grepl("t_insert|date_" , colnames(rt))]
-#get & import dsa: the main survey data file (containing only recnum, status, lurker and all variables relating to answers to survey questions)
-dsa.file <- paste0("modules/mod_uporabnost/temp/data_", ID, ".csv")
-dsa <- fread(dsa.file, header=T, drop=c(1:5, 7, 8))
+# čas v sekundah, ki ga je anketiranec preživel na x strani
+# (ki se izračuna kot razlika med stolpcem date_x in date_x+1)
+makeTime <- function(x) {
+ as.POSIXct(x, format = "%d.%m.%Y %H:%M:%S")
+}
+dat <- apply(times, 2, makeTime)
+response_times <- mapply(x = 2:ncol(dat),
+ y = 1:(ncol(dat) - 1),
+ function(x, y)
+ (dat)[, x] - (dat)[, y])
+
+
+# Zamenjamo ure in minute s sekundami
+rt[, grepl("t_insert|date_" , colnames(rt))] <- cbind(response_times, NA)
+rt[, grepl("t_insert|date_" , colnames(rt))][rt[, grepl("t_insert|date_" , colnames(rt))] < 0] <-
+ NA
+
+
+##################################################################
+## RT preparation ##
+##################################################################
+# Nov we need to match Items/variables with survey pages
+# so we will know which items match response time per page
+# This is important in order to correctly calculate
+# response times and remove respondents (set missing) with
+# item nonresponse per item.
+
+# First subset columns with time per page
+rt.page <- rt[, grepl("t_insert|date_" , colnames(rt))]
+# Zadnji stolpec je NA kot rezultat odštevanje stolpcev
+rt.page[ncol(rt.page)] <- NULL
+#rt.page[3,2] <- 1
+
+
+# ROČNO!!!!!!!
+# Popravimo vrednost na strani 4, ki ni mešana
+# ampak -8, saj sta na eni strani dve vprašanji
+#, ki pa sta bili porazdeljeni 50-50.
+# rt$Q7a.1 <- ifelse(rt$Q7a.1== -2 & rt$Q7b.1 >=0, rt$Q7b.1, rt$Q7a.1)
+# rt$Q7b.1 <- NULL
+# questions <- questions[-26,]
+# # Enako velja za stran 20 torej "Q28a" "Q28b"
+# rt$Q28a <- ifelse(rt$Q28a== -2 & rt$Q28b >=0, rt$Q28b, rt$Q28a)
+# rt$Q28b <- NULL
+# questions <- questions[-136,]
+#----------------------------- // Data // --------------------------------#
-#get question and item files
-questions.file <- paste0("modules/mod_uporabnost/temp/questions_", ID, ".csv")
-items.file <- paste0("modules/mod_uporabnost/temp/items_", ID, ".csv")
+#---------------------
+test <- rt.page
+miss1 <- vector()
+miss2 <- vector()
+mesanaStranR <- list()
+find.na <- list()
+
+#' @1.Trunciranje
+for (i in 1:ncol(test)) {
+ test[test < 0] <- NA
+ quantiles <- quantile(test[, i], .95, na.rm = TRUE)
+ # pripraviš vektor, s katerim najdeš katere vrednosti si zamenjal szs NA
+ find.na[[i]] <- which(test[, i] > quantiles)
+ # najprej nadomestiš vrednosti, ki so večje od thresholda z NA
+ # browser()
+ test[, i][find.na[[i]]] <- NA
+}
-# Main & Output ------------------------------------------------------
-#generate survey structure
-survey.str <- gen.survey.str(colnames(dsa)[-(1)], questions.file, items.file)
-if(any(!(is.data.table(survey.str)), nrow(survey.str)==0)){
- write(survey.str, paste0("modules/mod_uporabnost/results/usability_", ID, ".csv"))
-}else{
- #delete invisible variables and types: 5, 9, 22, 23, 25
- survey.str <- survey.str[visible==1 & !(tip %in% c(5, 9, 22, 23, 25)),]
+# We do not start with 0 because it is introduction page
+for(i in 1: ncol(test)) {
+ #' @2.Strani, ki so nagovori se pri izračunu indeksa ne upošteva
+ Ques.item <-
+ Ques.item[!grepl("nagovorLine=0", Ques.item$params), ]
+
+ #' @param 2: Set missing response time per page
+ # Split variables acording to page
+ var.per.page <- split(Ques.item, Ques.item$`ID PAGE`)
+ # Find number of variables per page
+ var.lab <- var.per.page[[i]][c("variable.x", "variable.y")]
+ # Only valid items
+ var.lab <- var.lab[var.lab > 1]
+
+ #' @3.Preverimo ali obstaja mešana stran
+ page.q <- rt %>% select(any_of(var.lab))
+ if(ncol(page.q) > 1) {
+ page.q <- page.q[, order(colnames(page.q))]
+ }
+ mesanaStranR[[i]] <-
+ data.frame(R=apply(page.q, 1, function(x)
+ ifelse(-2 %in% x & any(x > 0), "YES", "NO")))
+
+ #' @Vasja_2
+ #' Za te »mešane strani« nato pogledate vsakega respondenta
+ #' in greste skozi vse njegove iteme na tej strani:
+
+ #- Če ima item -2, ga spremenite v -7.
+
+ #- Če ima item -1, ga pusite pri miru
- #generate usability matrix
- m.all <- gen.usability.matrix(dsa, survey.str)
-
- if(any(!(is.data.table(m.all)), nrow(m.all)==0)){
- write(m.all, paste0("modules/mod_uporabnost/results/usability_", ID, ".csv"))
- }else{
- #calculate usability indexes
- m.final <- calc.usability(m.all, 3)
+ #- Če item ni mešan, ga pustite pri miru.
+ if (any(mesanaStranR[[i]] == "YES")) {
+ # -7
+ page.q[page.q == -2] <- -7
- #write to results
- write.csv2(m.final, paste0("modules/mod_uporabnost/results/usability_", ID, ".csv"), row.names = FALSE)
+ for (j in 1:nrow(test)) {
+
+ test[j, i] <-
+ ifelse(any(page.q[j,] > 0) &
+ any(page.q[j,] == -7), test[j, i] * sum(
+ subset(
+ Ques.item,
+ variable.x == colnames(page.q)[page.q[j,] != -7] |
+ variable.y == colnames(page.q)[page.q[j,] != -7],
+ select = c("cas1KA.x", "cas1KA.y")
+ )
+ ), test[j, i])
+
+ }
}
+ #' @5.Preverimo ali so na strnai manjkajole vrednosti
+ for (j in 1:nrow(test)) {
+ test[j, i] <-
+ suppressWarnings(ifelse(any(page.q[j,] == -1) &
+ !is.na(test[j, i]), test[j, i] / sum(
+ subset(
+ Ques.item,
+ variable.x == colnames(page.q)[page.q[j, ] == -1] |
+ variable.y == colnames(page.q)[page.q[j, ] == -1],
+ select = c("cas1KA.x", "cas1KA.y")
+ )
+ ), test[j, i]))
+ }
+
}
-#}
\ No newline at end of file +
+#' @6.Nato izračunamo indeks respondenta (Rti), ki je izračunan tako, da vsot
+#' o strani respondenta (brez -2) delimo z vsoto median taistih strani.
+# Mediana
+med.per.page <- apply(test, 2, function(x)
+ median(x, na.rm = TRUE))
+
+Rti <- NULL
+
+Rt_i <- lapply(seq_len(nrow(test)), function(y) {
+ indx <- which(!is.na(test[y, ]))
+ if( length(indx) != 0) {
+ Rti[y] <-
+ round(sum(test[y, ][indx], na.rm = TRUE) / sum(med.per.page[indx], na.rm = TRUE), 3)
+ } else {
+ Rti[y] <- NA
+ }
+})
+# Rti korak I
+Rt.i <- do.call(rbind, Rt_i)
+
+
+
+#' @8. Vrednosti, ki smo jih v prvem koraku truncirali imputiramo, in sicer so
+#' truncirane vrednosti zmnožek indeksa posameznega respondenta pomnožene z mediano
+#' strani oziroma Rti * mediana stranii
+
+imput.time <- test
+
+for(i in 1:length(med.per.page)) {
+ for (j in 1:nrow(test)) {
+ imput.time[find.na[[i]], i] <- Rt.i[find.na[[i]]] * med.per.page[i]
+ }
+}
+
+
+# Potem naredite novo datoteko z modificiranimi
+# PRAVIMI RT na stran ter dodamo imena stolpcev, ki
+# odražajo strani
+colnames(imput.time) <- paste("date_", 1:ncol(imput.time))
+# Zapišemo za prikaz v tabeli in prenos s strani uporabnika.
+write.csv2(imput.time, paste0("modules/mod_kakovost/results/rt_", ID, ".csv"), row.names = FALSE)
diff --git a/admin/survey/modules/mod_kakovost/class.SurveyKakovost.php b/admin/survey/modules/mod_kakovost/class.SurveyKakovost.php index 711bdd7..ec86761 100644 --- a/admin/survey/modules/mod_kakovost/class.SurveyKakovost.php +++ b/admin/survey/modules/mod_kakovost/class.SurveyKakovost.php @@ -50,9 +50,7 @@ class SurveyKakovost{ # polovimo vrsto tabel (aktivne / neaktivne)
SurveyInfo :: getInstance()->SurveyInit($this->anketa);
- if (SurveyInfo::getInstance()->getSurveyColumn('db_table') == 1) {
- $this->db_table = '_active';
- }
+ $this->db_table = SurveyInfo::getInstance()->getSurveyArchiveDBString();
SurveyAnalysisHelper::getInstance()->Init($this->anketa);
@@ -377,7 +375,7 @@ class SurveyKakovost{ // Testiranje - izpis errorjev
if($admin_type == 0){
- echo '<div style="display:none;">';
+ echo '<div>';
echo 'Rscript '.$script;
//echo '<br />'.$out.'<br />';
var_dump($output);
@@ -392,7 +390,7 @@ class SurveyKakovost{ $result_folder = $site_path . RESULTS_FOLDER.'/';
- if (($handle = fopen($result_folder."usability_".$this->anketa.".csv", "r")) !== FALSE) {
+ if (($handle = fopen($result_folder."rt_".$this->anketa.".csv", "r")) !== FALSE) {
// Loop po vrsticah
$cnt = 0;
@@ -753,8 +751,8 @@ class SurveyKakovost{ }
// Pobrisemo CSV datoteko z rezultati
- if (file_exists($result_folder.'/usability_'.$this->anketa.'.csv')) {
- unlink($result_folder.'/usability_'.$this->anketa.'.csv');
+ if (file_exists($result_folder.'/rt_'.$this->anketa.'.csv')) {
+ unlink($result_folder.'/rt_'.$this->anketa.'.csv');
}
}
|