I dati di questo questionario vengono dal sito OpenPsychometrics. Questio questionario è stato sviluppato per la misura del Machiavellisimo, definto come segue in Christie & Geis (1970):
[MAchiavelism is] a tendency to manipulate others for personal gain, accompanied by a lack of concern for conventional morality, low emotional involvement in interpersonal relations, and a cynical view of human nature.
Di seguito, il codebook associato ai dati:
This data was collected using an online version of the MACH-IV developed by Richard Christie and Florence L. Geis. See Christie, R. & Geis, F. (1970) "Studies in Machiavellianism". NY: Academic Press.
Data collection took place July 2017 - March 2019.
The main body of the consisted of 20 questions. The text of those questions is below.
{
"Q1" : "Never tell anyone the real reason you did something unless it is useful to do so.",
"Q2" : "The best way to handle people is to tell them what they want to hear.",
"Q3" : "One should take action only when sure it is morally right.",
"Q4" : "Most people are basically good and kind.",
"Q5" : "It is safest to assume that all people have a vicious streak and it will come out when they are given a chance.",
"Q6" : "Honesty is the best policy in all cases.",
"Q7" : "There is no excuse for lying to someone else.",
"Q8" : "Generally speaking, people won't work hard unless they're forced to do so.",
"Q9" : "All in all, it is better to be humble and honest than to be important and dishonest.",
"Q10" : "When you ask someone to do something for you, it is best to give the real reasons for wanting it rather than giving reasons which carry more weight.",
"Q11" : "Most people who get ahead in the world lead clean, moral lives.",
"Q12" : "Anyone who completely trusts anyone else is asking for trouble.",
"Q13" : "The biggest difference between most criminals and other people is that the criminals are stupid enough to get caught.",
"Q14" : "Most people are brave.",
"Q15" : "It is wise to flatter important people.",
"Q16" : "It is possible to be good in all respects.",
"Q17" : "P.T. Barnum was wrong when he said that there's a sucker born every minute.",
"Q18" : "It is hard to get ahead without cutting corners here and there.",
"Q19" : "People suffering from incurable diseases should have the choice of being put painlessly to death.",
"Q20" : "Most people forget more easily the death of their parents than the loss of their property."
}
The questions were presented one at a time in a random order. Users responded to each item on a five point scale: 1=Sisagree, 2=Slightly disagree, 3=Neutral, 4=Slightly agree, 5=Agree.
Three values are recorded for each question. e.g.
Q1A - the user's answer
Q1I - the position of that item in the survey
Q1E - the time spend on that question in milliseconds
After the test body, users were asked if they would be willing to complete an additional research survey. This data only includes those who agreed to.
The optional survey included a variety of questions:
The Ten Item Personality Inventory was administered (see Gosling, S. D., Rentfrow, P. J., & Swann, W. B., Jr. (2003). A Very Brief Measure of the Big Five Personality Domains. Journal of Research in Personality, 37, 504-528.):
TIPI1 Extraverted, enthusiastic.
TIPI2 Critical, quarrelsome.
TIPI3 Dependable, self-disciplined.
TIPI4 Anxious, easily upset.
TIPI5 Open to new experiences, complex.
TIPI6 Reserved, quiet.
TIPI7 Sympathetic, warm.
TIPI8 Disorganized, careless.
TIPI9 Calm, emotionally stable.
TIPI10 Conventional, uncreative.
The TIPI items were rated "I see myself as:" _____ such that
1 = Disagree strongly
2 = Disagree moderately
3 = Disagree a little
4 = Neither agree nor disagree
5 = Agree a little
6 = Agree moderately
7 = Agree strongly
The following items were presented as a check-list and subjects were instructed "In the grid below, check all the words whose definitions you are sure you know":
VCL1 boat
VCL2 incoherent
VCL3 pallid
VCL4 robot
VCL5 audible
VCL6 cuivocal
VCL7 paucity
VCL8 epistemology
VCL9 florted
VCL10 decide
VCL11 pastiche
VCL12 verdid
VCL13 abysmal
VCL14 lucid
VCL15 betray
VCL16 funny
A value of 1 is checked, 0 means unchecked. The words at VCL6, VCL9, and VCL12 are not real words and can be used as a validity check.
A bunch more questions were then asked:
education "How much education have you completed?", 1=Less than high school, 2=High school, 3=University degree, 4=Graduate degree
urban "What type of area did you live when you were a child?", 1=Rural (country side), 2=Suburban, 3=Urban (town, city)
gender "What is your gender?", 1=Male, 2=Female, 3=Other
engnat "Is English your native language?", 1=Yes, 2=No
age "How many years old are you?"
hand "What hand do you use to write with?", 1=Right, 2=Left, 3=Both
religion "What is your religion?", 1=Agnostic, 2=Atheist, 3=Buddhist, 4=Christian (Catholic), 5=Christian (Mormon), 6=Christian (Protestant), 7=Christian (Other), 8=Hindu, 9=Jewish, 10=Muslim, 11=Sikh, 12=Other
orientation "What is your sexual orientation?", 1=Heterosexual, 2=Bisexual, 3=Homosexual, 4=Asexual, 5=Other
race "What is your race?", 10=Asian, 20=Arab, 30=Black, 40=Indigenous Australian, 50=Native American, 60=White, 70=Other
voted "Have you voted in a national election in the past year?", 1=Yes, 2=No
married "What is your marital status?", 1=Never married, 2=Currently married, 3=Previously married
familysize "Including you, how many children did your mother have?"
major "If you attended a university, what was your major (e.g. "psychology", "English", "civil engineering")?"
The following value were calculated by the server:
country the user's network location
screenw width of user's device in pixels
screenh width of user's device in pixels
The time spend on each page was recorded in seconds:
introelapse
testelapse
surveyelapse
Per comodità vi ho preparato un file di dati dove sono dipsonibili solo le effettive risposte al MACH-IV e al TIPI - Un test di personalità composto da 10 item per misurare le dimensioni del BIG-FIVE.
L’ultima variabile del dato è una variabile dicotomica \(\[0,1\]\). Capirete (forse) a cosa serve.
Per svolgere l’esercitazione, trovate qui il file di dati da importare in R:
library(tidyverse)
library(psych)
library(lavaan)
library(semPlot)
library(corrplot)
load("data.RData")Per questa esercitazione, facciamo finta di non sapere assolutamente nulla sul MACH, vogliamo validarlo noi e non sappiamo quante dimensioni latenti sono coinvolte.
Volendo valutare anche la validità della misura del MACH, è stata somministrata la scala TIPI (Ten Item Personality Inventory), che misura le 5 dimensioni del Big Five con 10 item (due per dimensione). Lo scoring del TIPI è come segue:
| Dimensione | Item |
|---|---|
| Extraversion (E) | 1 + 6R |
| Agreeableness (A) | 2R + 7 |
| Conscientiousness (C) | 3 + 8R |
| Emotional Stability (N) | 4R + 9 |
| Openness to Experience (O) | 5 + 10R |
Commenti?
tipi_alpha = NULL
for (i in 1:5) {
temp = psych::alpha(tipi[, c(i, i +5)])$total
tipi_alpha = rbind(tipi_alpha, temp)
}
rownames(tipi_alpha) = c("E", "A", "C", "N", "O")
for (i in 1:5) {
X = rowMeans(tipi[, c(i, i+1)])
assign(rownames(tipi_alpha)[i],
X)
}
# valori di alpha di Cronbach
apply(tipi_alpha, 2, round, digits = 3) raw_alpha std.alpha G6(smc) average_r S/N ase mean sd median_r
E 0.793 0.793 0.657 0.657 3.833 0.006 3.492 1.774 0.657
A 0.497 0.498 0.331 0.331 0.991 0.015 3.945 1.457 0.331
C 0.652 0.657 0.489 0.489 1.914 0.010 4.620 1.567 0.489
N 0.746 0.748 0.598 0.598 2.974 0.008 4.244 1.708 0.598
O 0.130 0.135 0.072 0.072 0.156 0.025 4.495 1.139 0.072# punteggi TIPI
tipiscore = data.frame(E, A, C, N, O)
head(tipiscore) E A C N O
1 2.5 4.5 6.0 5.0 3.0
2 5.0 6.5 5.5 5.5 4.0
3 3.0 3.5 5.0 6.0 6.0
4 2.0 2.0 2.5 4.5 5.0
5 2.0 2.0 2.0 4.0 3.5
6 4.5 3.0 5.0 7.0 4.0La variabile dicotomica filter serve per fare la cross validation. Va usata fin dalle analisi preliminari di tutti gli item per splittare in due il campione.
filter == 0filter == 1machpre = data[data$filter == 0, c(1:20)]
machpre$sbj = 1:nrow(machpre)
machprelong = pivot_longer(machpre, cols=!sbj)
mysum = machprelong %>%
group_by(name, value) %>%
summarise(prop = n()/nrow(machpre))
ggplot(mysum,
aes(x = value, y = prop, fill = factor(value))) + geom_bar(stat="identity") + facet_wrap(~name)
machcor = psych::polychoric(machpre[,-ncol(machpre)])$rho
corrplot(machcor, type="lower", is.corr = T, tl.cex = 0.85,
tl.col = "black",
title = "Correlazioni MACH",
mar = c(0, 0, 2, 0),
addgrid.col = "white")
O si decide di girare gli item e quindi andare avanti con l’ipotesi che sia effettivamente reverse di una stessa dimensione o si prende la decisione più drastica di tenere gli item così come sono e portare avanti entrambe le strade:
Materiale che può servire: