Идентификация с природой, ценностные ориентации и психологическое благополучие у молодежи России и Франции
author
08 май, 2024
date()## [1] "Wed May 8 20:44:21 2024"options(scipen = 999)Список переменных
Nationality - Страна
Sex - Пол
Age - Возраст
Child - Место жительства в детстве
Adult - Текущее место жительства
Психологическое благополучие
- W_PositiveRel
- W_Autonomy
- W_EnvMastery
- W_PersGrowth
- W_PurposeLife
- W_SelfAcceptance
- WellBeing
EnvIdentity
Ценности:
- V_Conformity
- V_tradition
- V_benevolence
- V_universalism
- V_Selfdirection
- V_Stimulation
- V_Hedonism
- V_Achievement
- V_Power
- V_Security
libraries
library(kableExtra)
library(reshape2)
library(ggplot2)
library(dplyr)##
## Присоединяю пакет: 'dplyr'## Следующий объект скрыт от 'package:kableExtra':
##
## group_rows## Следующие объекты скрыты от 'package:stats':
##
## filter, lag## Следующие объекты скрыты от 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(stats)
library(tidyr)##
## Присоединяю пакет: 'tidyr'## Следующий объект скрыт от 'package:reshape2':
##
## smithslibrary(readxl)
library(psych)##
## Присоединяю пакет: 'psych'## Следующие объекты скрыты от 'package:ggplot2':
##
## %+%, alphaData <- read_excel("Thesis_data.xlsx")
Data$Nationality <- factor(Data$Nationality, levels = c(0, 1), labels = c("France", "Russia"), ordered = FALSE)
Data$Sex <- factor(Data$Sex, levels = c(0, 1), labels = c("Female", "Male"), ordered = FALSE)
Data$Child <- factor(Data$Child, levels = c(1:4), ordered = TRUE, labels = c("City"
, "Town"
, "Village"
, "SmallVillage"
)
)
Data$Adult <- factor(Data$Adult, levels = c(1:4), ordered = TRUE, labels = c("City"
, "Town"
, "Village"
, "SmallVillage"
)
) Описательная статистика
summary(Data)## Nationality Sex Age Child Adult
## France:62 Female:64 Min. :19.00 City :49 City :85
## Russia:47 Male :45 1st Qu.:22.00 Town :26 Town : 7
## Median :24.00 Village :20 Village :13
## Mean :24.95 SmallVillage:14 SmallVillage: 4
## 3rd Qu.:27.00
## Max. :39.00
## W_PositiveRel W_Autonomy W_EnvMastery W_PersGrowth
## Min. :41.00 Min. :33.00 Min. :34.00 Min. :40.00
## 1st Qu.:52.00 1st Qu.:45.00 1st Qu.:43.00 1st Qu.:48.00
## Median :56.00 Median :50.00 Median :49.00 Median :53.00
## Mean :56.29 Mean :51.75 Mean :49.54 Mean :55.88
## 3rd Qu.:60.00 3rd Qu.:55.00 3rd Qu.:55.00 3rd Qu.:64.00
## Max. :81.00 Max. :82.00 Max. :71.00 Max. :80.00
## W_PurposeLife W_SelfAcceptance WellBeing EnvIdentity
## Min. :41.00 Min. :33.00 Min. :258.0 Min. :26.00
## 1st Qu.:50.00 1st Qu.:48.00 1st Qu.:303.0 1st Qu.:49.00
## Median :58.00 Median :57.00 Median :326.0 Median :61.00
## Mean :58.61 Mean :56.64 Mean :328.7 Mean :59.85
## 3rd Qu.:66.00 3rd Qu.:65.00 3rd Qu.:343.0 3rd Qu.:70.00
## Max. :81.00 Max. :83.00 Max. :447.0 Max. :85.00
## V_Conformity V_Tradition V_Benevolence V_Universalism
## Min. :0.800 Min. :0.000 Min. :2.000 Min. :2.500
## 1st Qu.:2.400 1st Qu.:2.000 1st Qu.:4.400 1st Qu.:4.130
## Median :3.200 Median :3.000 Median :5.000 Median :5.000
## Mean :3.167 Mean :3.095 Mean :4.985 Mean :4.962
## 3rd Qu.:3.800 3rd Qu.:4.000 3rd Qu.:5.600 3rd Qu.:5.880
## Max. :5.600 Max. :7.000 Max. :7.000 Max. :7.000
## V_Selfdirection V_Stimulation V_Hedonism V_Achievement
## Min. :2.800 Min. :0.330 Min. :0.330 Min. :1.250
## 1st Qu.:4.800 1st Qu.:3.330 1st Qu.:4.330 1st Qu.:3.250
## Median :5.400 Median :4.330 Median :5.000 Median :4.250
## Mean :5.345 Mean :4.339 Mean :4.975 Mean :4.266
## 3rd Qu.:6.000 3rd Qu.:5.330 3rd Qu.:6.000 3rd Qu.:5.250
## Max. :7.000 Max. :7.000 Max. :7.000 Max. :7.000
## V_Power V_Security
## Min. :-1.000 Min. :1.200
## 1st Qu.: 1.500 1st Qu.:3.600
## Median : 2.500 Median :4.400
## Mean : 2.711 Mean :4.461
## 3rd Qu.: 3.750 3rd Qu.:5.400
## Max. : 6.750 Max. :7.000table(Data$Nationality, Data$Child)##
## City Town Village SmallVillage
## France 22 16 14 10
## Russia 27 10 6 4table(Data$Nationality, Data$Adult)##
## City Town Village SmallVillage
## France 41 7 12 2
## Russia 44 0 1 2Гистограммы Для всех
for (var in c("W_Autonomy", "W_PositiveRel", "W_EnvMastery", "W_PersGrowth", "W_PurposeLife", "W_SelfAcceptance", "WellBeing")) {
p <- Data %>%
ggplot(aes_string(x = var)) +
geom_histogram(binwidth = 5) +
labs(title = "Histogram of Well-being Variables", x = var, y = "Count") +
theme_light()
print(p)
}## Warning: `aes_string()` was deprecated in ggplot2 3.0.0.
## ℹ Please use tidy evaluation idioms with `aes()`.
## ℹ See also `vignette("ggplot2-in-packages")` for more information.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
for (var in c("V_Conformity", "V_Tradition", "V_Benevolence", "V_Universalism", "V_Selfdirection", "V_Stimulation", "V_Hedonism", "V_Achievement", "V_Power", "V_Security")) {
p <- Data %>%
ggplot(aes_string(x = var)) +
geom_histogram(bins = 20) +
labs(title = "Histogram of Value Variables", x = var, y = "Count") +
theme_light()
print(p)
}
Гистограммы Для национальности
for (var in c("W_Autonomy", "W_PositiveRel", "W_EnvMastery", "W_PersGrowth", "W_PurposeLife", "W_SelfAcceptance", "WellBeing")) {
p <- Data %>%
ggplot(aes_string(x = var)) +
geom_histogram(binwidth = 5) +
facet_grid(cols = vars(Nationality)) +
labs(title = "Histogram of Well-being Variables", x = var, y = "Count") +
theme_light()
print(p)
}
for (var in c("V_Conformity", "V_Tradition", "V_Benevolence", "V_Universalism", "V_Selfdirection", "V_Stimulation", "V_Hedonism", "V_Achievement", "V_Power", "V_Security")) {
p <- Data %>%
ggplot(aes_string(x = var)) +
geom_histogram(bins = 20) +
facet_grid(cols = vars(Nationality)) +
labs(title = "Histogram of Value Variables", x = var, y = "Count") +
theme_light()
print(p)
}
Гистограммы Для пола и национальности
for (var in c("W_Autonomy", "W_PositiveRel", "W_EnvMastery", "W_PersGrowth", "W_PurposeLife", "W_SelfAcceptance", "WellBeing")) {
p <- Data %>%
ggplot(aes_string(x = var)) +
geom_histogram(binwidth = 5) +
facet_grid(rows = vars(Sex), cols = vars(Nationality)) +
labs(title = "Histogram of Well-being Variables", x = var, y = "Count") +
theme_light()
print(p)
}
for (var in c("V_Conformity", "V_Tradition", "V_Benevolence", "V_Universalism", "V_Selfdirection", "V_Stimulation", "V_Hedonism", "V_Achievement", "V_Power", "V_Security")) {
p <- Data %>%
ggplot(aes_string(x = var)) +
geom_histogram(bins = 20) +
facet_grid(rows = vars(Sex), cols = vars(Nationality)) +
labs(title = "Histogram of Value Variables", x = var, y = "Count") +
theme_light()
print(p)
}
## сравнение боксплотов для фр и рус
Data %>%
select(1:11) %>% # Берем только первые 11 колонок
pivot_longer(cols = starts_with("W_"), names_to = "Variable", values_to = "Value") %>% # Колонки, которые начинаются с "W_"
ggplot(., aes(x = Variable, y = Value, fill = Nationality)) +
geom_boxplot() +
labs(title = " ", x = "Психолгическое благополучие", y = "Значение") +
theme_light() +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
scale_x_discrete(labels = c("Позитивные\nотношения", "Автономность", "Управление\nсредой", "Персональное\nразвитие", "Цель в\nжизни", "Самопринятие")) +
scale_fill_manual(name = "Страна: ",
values = c("France" = "#F8766D",
"Russia" = "#619CFF"),
labels = c("France" = "Франция",
"Russia" = "Россия")) +
theme(text = element_text(size = 13),
legend.position = 'top',
legend.title = element_text(hjust = 0.5, margin = margin(t = 10, b = 10)))
Data %>%
pivot_longer(cols = starts_with("V_"), names_to = "Variable", values_to = "Value") %>%
ggplot(., aes(x = Variable, y = Value, fill = Nationality)) +
geom_boxplot() +
labs(title = " ", x = "Ценностные ориентации", y = "Значение") +
theme_light() +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
scale_x_discrete(labels = c("Конформность", "Традиции", "Доброта", "Универсализм", "Личностный рост", "Стимуляция", "Гедонизм", "Достижения", "Власть", "Безопасность")) +
scale_fill_manual(name = "Страна: ",
values = c("France" = "#F8766D",
"Russia" = "#619CFF"),
labels = c("France" = "Франция",
"Russia" = "Россия")) +
theme(text = element_text(size = 13),
legend.position = 'top',
legend.title = element_text(hjust = 0.5, margin = margin(t = 10, b = 10)))
средние и ст отклонение для рус фр, рус ж фр ж, рус м фр м
# Define function to generate descriptive table for multiple subsets
descriptive_table <- function(data, subset_names) {
tables <- lapply(subset_names, function(subset_name) {
subset_data <- subset_data(data, subset_name)
subset_mean <- sapply(subset_data, function(x) if(is.numeric(x)) mean(x) else NA)
subset_sd <- sapply(subset_data, function(x) if(is.numeric(x)) sd(x) else NA)
data.frame(Mean = subset_mean, SD = subset_sd)
})
do.call(rbind, tables)
}
# Define function to subset data
subset_data <- function(data, subset_name) {
switch(
subset_name,
France = subset(data, Nationality == "France"),
Russia = subset(data, Nationality == "Russia"),
FranceMale = subset(data, Nationality == "France" & Sex == "Male"),
FranceFemale = subset(data, Nationality == "France" & Sex == "Female"),
RussiaMale = subset(data, Nationality == "Russia" & Sex == "Male"),
RussiaFemale = subset(data, Nationality == "Russia" & Sex == "Female")
)
}
subset_names <- c("Data", "France", "Russia", "FranceMale", "FranceFemale", 'RussiaMale', 'RussiaFemale')
descriptive_table_multiple <- descriptive_table(Data, subset_names)
print(descriptive_table_multiple)## Mean SD
## Nationality NA NA
## Sex NA NA
## Age 25.064516 5.0760478
## Child NA NA
## Adult NA NA
## W_PositiveRel 54.596774 5.2274800
## W_Autonomy 47.322581 4.7105539
## W_EnvMastery 44.451613 5.2344302
## W_PersGrowth 49.387097 4.0218862
## W_PurposeLife 58.258065 9.9208928
## W_SelfAcceptance 56.258065 11.4389835
## WellBeing 310.274194 23.1347934
## EnvIdentity 59.838710 12.8116156
## V_Conformity 3.454839 1.0895446
## V_Tradition 3.664516 1.3807929
## V_Benevolence 5.267742 0.9560462
## V_Universalism 5.251935 1.0799998
## V_Selfdirection 5.445161 1.0659680
## V_Stimulation 4.714516 1.5557674
## V_Hedonism 5.086129 1.2739114
## V_Achievement 4.310484 1.3832172
## V_Power 2.713710 1.5777960
## V_Security 4.661290 1.4708484
## Nationality1 NA NA
## Sex1 NA NA
## Age1 24.808511 4.0412993
## Child1 NA NA
## Adult1 NA NA
## W_PositiveRel1 58.531915 9.6927832
## W_Autonomy1 57.595745 8.8210706
## W_EnvMastery1 56.255319 7.8808190
## W_PersGrowth1 64.446809 6.7237687
## W_PurposeLife1 59.085106 9.3036454
## W_SelfAcceptance1 57.148936 10.5294178
## WellBeing1 353.063830 39.9871742
## EnvIdentity1 59.872340 12.5223574
## V_Conformity1 2.787234 0.9774895
## V_Tradition1 2.344681 1.3284199
## V_Benevolence1 4.612766 1.0659996
## V_Universalism1 4.579787 1.1118267
## V_Selfdirection1 5.212766 0.8581114
## V_Stimulation1 3.844043 1.4069311
## V_Hedonism1 4.829362 1.3264556
## V_Achievement1 4.207447 1.1660030
## V_Power1 2.707447 1.6313164
## V_Security1 4.195745 0.9486735
## Nationality2 NA NA
## Sex2 NA NA
## Age2 26.400000 4.9328829
## Child2 NA NA
## Adult2 NA NA
## W_PositiveRel2 55.640000 4.3193364
## W_Autonomy2 47.400000 4.6992907
## W_EnvMastery2 43.800000 5.5226805
## W_PersGrowth2 48.120000 3.8656608
## W_PurposeLife2 60.160000 9.7625133
## W_SelfAcceptance2 58.320000 12.0163777
## WellBeing2 313.440000 20.4818619
## EnvIdentity2 55.720000 12.4616746
## V_Conformity2 3.184000 1.0565983
## V_Tradition2 3.320000 1.3625956
## V_Benevolence2 5.048000 0.9544283
## V_Universalism2 5.002800 0.8974246
## V_Selfdirection2 5.520000 0.9165151
## V_Stimulation2 4.800000 1.3678542
## V_Hedonism2 5.200000 0.9954563
## V_Achievement2 4.310000 1.1732256
## V_Power2 2.680000 1.4974284
## V_Security2 4.784000 1.3927431
## Nationality3 NA NA
## Sex3 NA NA
## Age3 24.162162 5.0360562
## Child3 NA NA
## Adult3 NA NA
## W_PositiveRel3 53.891892 5.7095621
## W_Autonomy3 47.270270 4.7821929
## W_EnvMastery3 44.891892 5.0595552
## W_PersGrowth3 50.243243 3.9469074
## W_PurposeLife3 56.972973 9.9512324
## W_SelfAcceptance3 54.864865 10.9776595
## WellBeing3 308.135135 24.8105736
## EnvIdentity3 62.621622 12.4439886
## V_Conformity3 3.637838 1.0871347
## V_Tradition3 3.897297 1.3618791
## V_Benevolence3 5.416216 0.9408960
## V_Universalism3 5.420270 1.1692982
## V_Selfdirection3 5.394595 1.1657010
## V_Stimulation3 4.656757 1.6868314
## V_Hedonism3 5.009189 1.4401801
## V_Achievement3 4.310811 1.5245735
## V_Power3 2.736486 1.6498589
## V_Security3 4.578378 1.5346254
## Nationality4 NA NA
## Sex4 NA NA
## Age4 27.600000 4.1977438
## Child4 NA NA
## Adult4 NA NA
## W_PositiveRel4 57.250000 9.4081432
## W_Autonomy4 61.850000 8.4683622
## W_EnvMastery4 54.850000 9.0220490
## W_PersGrowth4 63.900000 8.1233905
## W_PurposeLife4 57.150000 10.1373463
## W_SelfAcceptance4 56.750000 11.5752686
## WellBeing4 351.750000 42.9784218
## EnvIdentity4 58.200000 10.3902789
## V_Conformity4 2.820000 1.0620734
## V_Tradition4 2.420000 1.4095912
## V_Benevolence4 4.550000 1.1199154
## V_Universalism4 4.384500 1.1816112
## V_Selfdirection4 5.230000 0.9342039
## V_Stimulation4 3.900000 1.1996622
## V_Hedonism4 4.716000 1.5278378
## V_Achievement4 4.100000 1.2576084
## V_Power4 2.350000 1.8872843
## V_Security4 4.000000 0.9267941
## Nationality5 NA NA
## Sex5 NA NA
## Age5 22.740741 2.3630585
## Child5 NA NA
## Adult5 NA NA
## W_PositiveRel5 59.481481 9.9667539
## W_Autonomy5 54.444444 7.8118910
## W_EnvMastery5 57.296296 6.9104982
## W_PersGrowth5 64.851852 5.6001628
## W_PurposeLife5 60.518519 8.5456708
## W_SelfAcceptance5 57.444444 9.9007899
## WellBeing5 354.037037 38.4292371
## EnvIdentity5 61.111111 13.9568933
## V_Conformity5 2.762963 0.9299082
## V_Tradition5 2.288889 1.2894046
## V_Benevolence5 4.659259 1.0433892
## V_Universalism5 4.724444 1.0562573
## V_Selfdirection5 5.200000 0.8152395
## V_Stimulation5 3.802593 1.5640347
## V_Hedonism5 4.913333 1.1789402
## V_Achievement5 4.287037 1.1109241
## V_Power5 2.972222 1.3907893
## V_Security5 4.340741 0.9556549ю-тест. россия и франци. без деления на пол
russian <- subset(Data, Nationality == 'Russia')
french <- subset(Data, Nationality == "France")
numeric_data_fr <- russian[sapply(russian, is.numeric)]
numeric_data_rus <- french[sapply(french, is.numeric)]
test_results <- data.frame(Variable = character(),
Statistic = numeric(),
p_value = numeric(),
stringsAsFactors = FALSE)
for (col in names(numeric_data_rus)) {
test_result <- wilcox.test(numeric_data_rus[[col]], numeric_data_fr[[col]], exact = FALSE)
test_results <- rbind(test_results,
data.frame(Variable = col,
Statistic = test_result$statistic,
p_value = test_result$p.value))
}
print(test_results)## Variable Statistic p_value
## W Age 1407.0 0.76091732682271262522278
## W1 W_PositiveRel 1111.5 0.03455242911204069178321
## W2 W_Autonomy 425.0 0.00000000025839638949183
## W3 W_EnvMastery 322.0 0.00000000000370075517420
## W4 W_PersGrowth 80.0 0.00000000000000003443398
## W5 W_PurposeLife 1405.5 0.75484660166107520051781
## W6 W_SelfAcceptance 1381.0 0.64388326379770788321366
## W7 WellBeing 511.5 0.00000000734352084766878
## W8 EnvIdentity 1474.0 0.91953571231547903686021
## W9 V_Conformity 1988.5 0.00112604054899900080100
## W10 V_Tradition 2214.5 0.00000352218617667844349
## W11 V_Benevolence 1917.5 0.00476974278045354509875
## W12 V_Universalism 1952.5 0.00242865988142633004027
## W13 V_Selfdirection 1697.0 0.14184916263340840991702
## W14 V_Stimulation 1927.5 0.00394224998536743531652
## W15 V_Hedonism 1590.0 0.41573555317117349972023
## W16 V_Achievement 1532.0 0.64793831620696029638395
## W17 V_Power 1463.0 0.97310907449596739660080
## W18 V_Security 1767.0 0.05782807333616002409826Корреляции (сравниваю все со всем, тк не придумала, как не сравнивать подшкалы внутри одной методики)
Для всех
numeric_data <- Data[sapply(Data, is.numeric)]
correlation_matrix <- cor(numeric_data)
p_values <- matrix(NA, nrow = ncol(numeric_data), ncol = ncol(numeric_data))
rownames(p_values) <- colnames(p_values) <- colnames(numeric_data)
for (i in 1:(ncol(numeric_data) - 1)) {
for (j in (i + 1):ncol(numeric_data)) {
cor_test_result <- cor.test(numeric_data[[i]], numeric_data[[j]])
p_values[i, j] <- p_values[j, i] <- cor_test_result$p.value
}
}
significant_level <- 0.05
significant <- ifelse(p_values < significant_level, "*", "")
cor_matrix_with_significance <- round(correlation_matrix, 2)
cor_matrix_with_significance[lower.tri(cor_matrix_with_significance)] <- paste(cor_matrix_with_significance[lower.tri(cor_matrix_with_significance)], significant[lower.tri(significant)], sep = "")
cor_thes <- as.data.frame(cor_matrix_with_significance)
cor_thes <- cor_thes[-1, -1]
kable(cor_thes, format = "html") %>%
kable_styling()| W_PositiveRel | W_Autonomy | W_EnvMastery | W_PersGrowth | W_PurposeLife | W_SelfAcceptance | WellBeing | EnvIdentity | V_Conformity | V_Tradition | V_Benevolence | V_Universalism | V_Selfdirection | V_Stimulation | V_Hedonism | V_Achievement | V_Power | V_Security | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| W_PositiveRel | 1 | 0.32 | 0.33 | 0.39 | 0.48 | 0.48 | 0.71 | 0.06 | 0.07 | -0.12 | 0.21 | 0.22 | 0.16 | 0.06 | 0.02 | 0.14 | -0.17 | 0.03 |
| W_Autonomy | 0.32* | 1 | 0.57 | 0.59 | 0.12 | 0.19 | 0.65 | -0.1 | -0.05 | -0.18 | -0.13 | -0.1 | -0.04 | -0.22 | -0.22 | 0.01 | -0.04 | -0.17 |
| W_EnvMastery | 0.33* | 0.57* | 1 | 0.71 | 0.26 | 0.24 | 0.73 | -0.07 | -0.09 | -0.22 | -0.15 | -0.26 | -0.18 | -0.36 | -0.22 | 0.05 | -0.01 | -0.21 |
| W_PersGrowth | 0.39* | 0.59* | 0.71* | 1 | 0.16 | 0.1 | 0.69 | 0.07 | -0.2 | -0.33 | -0.14 | -0.14 | -0.01 | -0.18 | -0.21 | 0.03 | -0.03 | -0.16 |
| W_PurposeLife | 0.48* | 0.12 | 0.26* | 0.16 | 1 | 0.71 | 0.68 | 0.02 | 0.09 | 0.1 | 0.2 | 0.2 | 0.37 | 0.21 | -0.02 | 0.33 | 0.03 | 0.19 |
| W_SelfAcceptance | 0.48* | 0.19* | 0.24* | 0.1 | 0.71* | 1 | 0.69 | 0.09 | 0.22 | 0.18 | 0.34 | 0.33 | 0.36 | 0.2 | 0.05 | 0.22 | 0.04 | 0.25 |
| WellBeing | 0.71* | 0.65* | 0.73* | 0.69* | 0.68* | 0.69* | 1 | 0.02 | 0.02 | -0.12 | 0.1 | 0.08 | 0.18 | -0.05 | -0.14 | 0.2 | -0.03 | 0 |
| EnvIdentity | 0.06 | -0.1 | -0.07 | 0.07 | 0.02 | 0.09 | 0.02 | 1 | 0.26 | 0.26 | 0.35 | 0.44 | 0.21 | 0.1 | 0.11 | 0.11 | -0.06 | 0.25 |
| V_Conformity | 0.07 | -0.05 | -0.09 | -0.2* | 0.09 | 0.22* | 0.02 | 0.26* | 1 | 0.71 | 0.61 | 0.48 | 0.46 | 0.28 | 0.2 | 0.55 | 0.39 | 0.59 |
| V_Tradition | -0.12 | -0.18 | -0.22* | -0.33* | 0.1 | 0.18 | -0.12 | 0.26* | 0.71* | 1 | 0.52 | 0.48 | 0.4 | 0.33 | 0.1 | 0.36 | 0.33 | 0.44 |
| V_Benevolence | 0.21* | -0.13 | -0.15 | -0.14 | 0.2* | 0.34* | 0.1 | 0.35* | 0.61* | 0.52* | 1 | 0.62 | 0.57 | 0.39 | 0.27 | 0.49 | 0.11 | 0.42 |
| V_Universalism | 0.22* | -0.1 | -0.26* | -0.14 | 0.2* | 0.33* | 0.08 | 0.44* | 0.48* | 0.48* | 0.62* | 1 | 0.59 | 0.37 | 0.2 | 0.25 | 0.01 | 0.42 |
| V_Selfdirection | 0.16 | -0.04 | -0.18 | -0.01 | 0.37* | 0.36* | 0.18 | 0.21* | 0.46* | 0.4* | 0.57* | 0.59* | 1 | 0.48 | 0.35 | 0.5 | 0.21 | 0.47 |
| V_Stimulation | 0.06 | -0.22* | -0.36* | -0.18 | 0.21* | 0.2* | -0.05 | 0.1 | 0.28* | 0.33* | 0.39* | 0.37* | 0.48* | 1 | 0.41 | 0.44 | 0.4 | 0.43 |
| V_Hedonism | 0.02 | -0.22* | -0.22* | -0.21* | -0.02 | 0.05 | -0.14 | 0.11 | 0.2* | 0.1 | 0.27* | 0.2* | 0.35* | 0.41* | 1 | 0.42 | 0.32 | 0.43 |
| V_Achievement | 0.14 | 0.01 | 0.05 | 0.03 | 0.33* | 0.22* | 0.2* | 0.11 | 0.55* | 0.36* | 0.49* | 0.25* | 0.5* | 0.44* | 0.42* | 1 | 0.56 | 0.45 |
| V_Power | -0.17 | -0.04 | -0.01 | -0.03 | 0.03 | 0.04 | -0.03 | -0.06 | 0.39* | 0.33* | 0.11 | 0.01 | 0.21* | 0.4* | 0.32* | 0.56* | 1 | 0.41 |
| V_Security | 0.03 | -0.17 | -0.21* | -0.16 | 0.19* | 0.25* | 0 | 0.25* | 0.59* | 0.44* | 0.42* | 0.42* | 0.47* | 0.43* | 0.43* | 0.45* | 0.41* | 1 |
Россия
numeric_data <- russian[sapply(russian, is.numeric)]
correlation_matrix <- cor(numeric_data)
p_values <- matrix(NA, nrow = ncol(numeric_data), ncol = ncol(numeric_data))
rownames(p_values) <- colnames(p_values) <- colnames(numeric_data)
for (i in 1:(ncol(numeric_data) - 1)) {
for (j in (i + 1):ncol(numeric_data)) {
cor_test_result <- cor.test(numeric_data[[i]], numeric_data[[j]])
p_values[i, j] <- p_values[j, i] <- cor_test_result$p.value
}
}
significant_level <- 0.05
significant <- ifelse(p_values < significant_level, "*", "")
cor_matrix_with_significance <- round(correlation_matrix, 2)
cor_matrix_with_significance[lower.tri(cor_matrix_with_significance)] <- paste(cor_matrix_with_significance[lower.tri(cor_matrix_with_significance)], significant[lower.tri(significant)], sep = "")
cor_thes <- as.data.frame(cor_matrix_with_significance)
cor_thes <- cor_thes[-1, -1]
kable(cor_thes, format = "html") %>%
kable_styling()| W_PositiveRel | W_Autonomy | W_EnvMastery | W_PersGrowth | W_PurposeLife | W_SelfAcceptance | WellBeing | EnvIdentity | V_Conformity | V_Tradition | V_Benevolence | V_Universalism | V_Selfdirection | V_Stimulation | V_Hedonism | V_Achievement | V_Power | V_Security | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| W_PositiveRel | 1 | 0.3 | 0.43 | 0.52 | 0.4 | 0.46 | 0.7 | 0.09 | 0.25 | -0.06 | 0.45 | 0.31 | 0.1 | 0.1 | 0.1 | 0.26 | -0.25 | 0.09 |
| W_Autonomy | 0.3* | 1 | 0.39 | 0.36 | 0.35 | 0.47 | 0.64 | -0.22 | 0.14 | 0.08 | 0.18 | 0.16 | 0.14 | 0.03 | -0.34 | 0.02 | -0.22 | -0.09 |
| W_EnvMastery | 0.43* | 0.39* | 1 | 0.53 | 0.65 | 0.65 | 0.8 | -0.04 | 0.3 | 0.15 | 0.26 | 0.11 | 0.11 | -0.01 | -0.17 | 0.25 | 0.04 | 0.03 |
| W_PersGrowth | 0.52* | 0.36* | 0.53* | 1 | 0.57 | 0.58 | 0.76 | 0.23 | 0.18 | 0.12 | 0.4 | 0.42 | 0.39 | 0.25 | -0.19 | 0.26 | -0.04 | 0.16 |
| W_PurposeLife | 0.4* | 0.35* | 0.65* | 0.57* | 1 | 0.6 | 0.79 | 0.12 | 0.06 | 0.1 | 0.28 | 0.16 | 0.28 | 0.07 | -0.21 | 0.38 | 0.03 | 0.07 |
| W_SelfAcceptance | 0.46* | 0.47* | 0.65* | 0.58* | 0.6* | 1 | 0.84 | 0.09 | 0.34 | 0.16 | 0.42 | 0.4 | 0.3 | 0.12 | -0.25 | 0.16 | 0.03 | 0.16 |
| WellBeing | 0.7* | 0.64* | 0.8* | 0.76* | 0.79* | 0.84* | 1 | 0.05 | 0.29 | 0.12 | 0.45 | 0.34 | 0.29 | 0.12 | -0.23 | 0.29 | -0.09 | 0.09 |
| EnvIdentity | 0.09 | -0.22 | -0.04 | 0.23 | 0.12 | 0.09 | 0.05 | 1 | 0.28 | 0.27 | 0.24 | 0.43 | 0.26 | 0.09 | 0.17 | 0.18 | 0.08 | 0.46 |
| V_Conformity | 0.25 | 0.14 | 0.3* | 0.18 | 0.06 | 0.34* | 0.29 | 0.28 | 1 | 0.59 | 0.58 | 0.47 | 0.39 | 0.11 | 0 | 0.42 | 0.15 | 0.57 |
| V_Tradition | -0.06 | 0.08 | 0.15 | 0.12 | 0.1 | 0.16 | 0.12 | 0.27 | 0.59* | 1 | 0.37 | 0.44 | 0.41 | 0.23 | -0.11 | 0.3 | 0.32 | 0.33 |
| V_Benevolence | 0.45* | 0.18 | 0.26 | 0.4* | 0.28 | 0.42* | 0.45* | 0.24 | 0.58* | 0.37* | 1 | 0.58 | 0.52 | 0.16 | 0.22 | 0.47 | 0.07 | 0.34 |
| V_Universalism | 0.31* | 0.16 | 0.11 | 0.42* | 0.16 | 0.4* | 0.34* | 0.43* | 0.47* | 0.44* | 0.58* | 1 | 0.57 | 0.09 | -0.02 | 0.21 | -0.02 | 0.59 |
| V_Selfdirection | 0.1 | 0.14 | 0.11 | 0.39* | 0.28 | 0.3* | 0.29 | 0.26 | 0.39* | 0.41* | 0.52* | 0.57* | 1 | 0.32 | 0.11 | 0.44 | 0.16 | 0.43 |
| V_Stimulation | 0.1 | 0.03 | -0.01 | 0.25 | 0.07 | 0.12 | 0.12 | 0.09 | 0.11 | 0.23 | 0.16 | 0.09 | 0.32* | 1 | 0.23 | 0.34 | 0.49 | 0.12 |
| V_Hedonism | 0.1 | -0.34* | -0.17 | -0.19 | -0.21 | -0.25 | -0.23 | 0.17 | 0 | -0.11 | 0.22 | -0.02 | 0.11 | 0.23 | 1 | 0.24 | 0.18 | 0.1 |
| V_Achievement | 0.26 | 0.02 | 0.25 | 0.26 | 0.38* | 0.16 | 0.29* | 0.18 | 0.42* | 0.3* | 0.47* | 0.21 | 0.44* | 0.34* | 0.24 | 1 | 0.47 | 0.26 |
| V_Power | -0.25 | -0.22 | 0.04 | -0.04 | 0.03 | 0.03 | -0.09 | 0.08 | 0.15 | 0.32* | 0.07 | -0.02 | 0.16 | 0.49* | 0.18 | 0.47* | 1 | 0.19 |
| V_Security | 0.09 | -0.09 | 0.03 | 0.16 | 0.07 | 0.16 | 0.09 | 0.46* | 0.57* | 0.33* | 0.34* | 0.59* | 0.43* | 0.12 | 0.1 | 0.26 | 0.19 | 1 |
Франция
numeric_data <- french[sapply(french, is.numeric)]
correlation_matrix <- cor(numeric_data)
p_values <- matrix(NA, nrow = ncol(numeric_data), ncol = ncol(numeric_data))
rownames(p_values) <- colnames(p_values) <- colnames(numeric_data)
for (i in 1:(ncol(numeric_data) - 1)) {
for (j in (i + 1):ncol(numeric_data)) {
cor_test_result <- cor.test(numeric_data[[i]], numeric_data[[j]])
p_values[i, j] <- p_values[j, i] <- cor_test_result$p.value
}
}
significant_level <- 0.05
significant <- ifelse(p_values < significant_level, "*", "")
cor_matrix_with_significance <- round(correlation_matrix, 2)
cor_matrix_with_significance[lower.tri(cor_matrix_with_significance)] <- paste(cor_matrix_with_significance[lower.tri(cor_matrix_with_significance)], significant[lower.tri(significant)], sep = "")
cor_thes <- as.data.frame(cor_matrix_with_significance)
cor_thes <- cor_thes[-1, -1]
kable(cor_thes, format = "html") %>%
kable_styling()| W_PositiveRel | W_Autonomy | W_EnvMastery | W_PersGrowth | W_PurposeLife | W_SelfAcceptance | WellBeing | EnvIdentity | V_Conformity | V_Tradition | V_Benevolence | V_Universalism | V_Selfdirection | V_Stimulation | V_Hedonism | V_Achievement | V_Power | V_Security | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| W_PositiveRel | 1 | -0.03 | -0.2 | -0.15 | 0.67 | 0.6 | 0.73 | 0.03 | 0.06 | 0.07 | 0.12 | 0.37 | 0.35 | 0.21 | -0.02 | 0.07 | -0.08 | 0.09 |
| W_Autonomy | -0.03 | 1 | 0.07 | -0.09 | -0.18 | -0.1 | 0.07 | -0.03 | 0.23 | 0.18 | -0.08 | 0.02 | -0.06 | -0.2 | -0.03 | 0.08 | 0.21 | -0.09 |
| W_EnvMastery | -0.2 | 0.07 | 1 | 0.07 | -0.04 | -0.08 | 0.15 | -0.16 | 0.03 | 0.07 | -0.14 | -0.31 | -0.39 | -0.5 | -0.26 | -0.03 | -0.06 | -0.26 |
| W_PersGrowth | -0.15 | -0.09 | 0.07 | 1 | -0.17 | -0.4 | -0.13 | -0.01 | 0 | -0.02 | -0.07 | -0.1 | -0.07 | -0.07 | -0.28 | -0.04 | -0.07 | -0.18 |
| W_PurposeLife | 0.67* | -0.18 | -0.04 | -0.17 | 1 | 0.78 | 0.89 | -0.05 | 0.13 | 0.15 | 0.19 | 0.27 | 0.44 | 0.33 | 0.13 | 0.31 | 0.02 | 0.27 |
| W_SelfAcceptance | 0.6* | -0.1 | -0.08 | -0.4* | 0.78* | 1 | 0.86 | 0.09 | 0.19 | 0.26 | 0.35 | 0.32 | 0.41 | 0.29 | 0.28 | 0.26 | 0.05 | 0.32 |
| WellBeing | 0.73* | 0.07 | 0.15 | -0.13 | 0.89* | 0.86* | 1 | -0.01 | 0.22 | 0.26 | 0.22 | 0.28 | 0.36 | 0.17 | 0.08 | 0.28 | 0.03 | 0.18 |
| EnvIdentity | 0.03 | -0.03 | -0.16 | -0.01 | -0.05 | 0.09 | -0.01 | 1 | 0.27 | 0.29 | 0.47 | 0.49 | 0.18 | 0.12 | 0.07 | 0.07 | -0.17 | 0.16 |
| V_Conformity | 0.06 | 0.23 | 0.03 | 0 | 0.13 | 0.19 | 0.22 | 0.27* | 1 | 0.72 | 0.56 | 0.4 | 0.48 | 0.29 | 0.31 | 0.64 | 0.59 | 0.58 |
| V_Tradition | 0.07 | 0.18 | 0.07 | -0.02 | 0.15 | 0.26* | 0.26* | 0.29* | 0.72* | 1 | 0.52 | 0.38 | 0.37 | 0.24 | 0.19 | 0.44 | 0.4 | 0.46 |
| V_Benevolence | 0.12 | -0.08 | -0.14 | -0.07 | 0.19 | 0.35* | 0.22 | 0.47* | 0.56* | 0.52* | 1 | 0.59 | 0.61 | 0.46 | 0.29 | 0.54 | 0.16 | 0.45 |
| V_Universalism | 0.37* | 0.02 | -0.31* | -0.1 | 0.27* | 0.32* | 0.28* | 0.49* | 0.4* | 0.38* | 0.59* | 1 | 0.61 | 0.47 | 0.34 | 0.28 | 0.03 | 0.31 |
| V_Selfdirection | 0.35* | -0.06 | -0.39* | -0.07 | 0.44* | 0.41* | 0.36* | 0.18 | 0.48* | 0.37* | 0.61* | 0.61* | 1 | 0.55 | 0.48 | 0.53 | 0.25 | 0.47 |
| V_Stimulation | 0.21 | -0.2 | -0.5* | -0.07 | 0.33* | 0.29* | 0.17 | 0.12 | 0.29* | 0.24 | 0.46* | 0.47* | 0.55* | 1 | 0.52 | 0.52 | 0.37 | 0.53 |
| V_Hedonism | -0.02 | -0.03 | -0.26* | -0.28* | 0.13 | 0.28* | 0.08 | 0.07 | 0.31* | 0.19 | 0.29* | 0.34* | 0.48* | 0.52* | 1 | 0.54 | 0.44 | 0.6 |
| V_Achievement | 0.07 | 0.08 | -0.03 | -0.04 | 0.31* | 0.26* | 0.28* | 0.07 | 0.64* | 0.44* | 0.54* | 0.28* | 0.53* | 0.52* | 0.54* | 1 | 0.62 | 0.54 |
| V_Power | -0.08 | 0.21 | -0.06 | -0.07 | 0.02 | 0.05 | 0.03 | -0.17 | 0.59* | 0.4* | 0.16 | 0.03 | 0.25* | 0.37* | 0.44* | 0.62* | 1 | 0.55 |
| V_Security | 0.09 | -0.09 | -0.26* | -0.18 | 0.27* | 0.32* | 0.18 | 0.16 | 0.58* | 0.46* | 0.45* | 0.31* | 0.47* | 0.53* | 0.6* | 0.54* | 0.55* | 1 |
Дисперсия и т-тест
Идентификация с природой и место жительства в детстве (значим различия 1\4, 2\4)
child_place1 <- subset(Data, Child == 'City')
child_place2 <- subset(Data, Child == 'Town')
child_place3 <- subset(Data, Child == 'Village')
child_place4 <- subset(Data, Child == 'SmallVillage')
data_list <- list(child_place1$EnvIdentity, child_place2$EnvIdentity, child_place3$EnvIdentity, child_place4$EnvIdentity)
boxplot(data_list, names = c("Мегаполис", "Город", "Маленький город", "Деревня"), main = "", xlab = "Место жительства в детстве", ylab = "Идентификация с природой", col = "skyblue", border = "black")
group1 <- child_place1$EnvIdentity
group2 <- child_place4$EnvIdentity
# Perform Shapiro-Wilk test for normality
shapiro_test_group1 <- shapiro.test(group1)
shapiro_test_group2 <- shapiro.test(group2)
# Decide which test to use based on the results of normality tests
if (shapiro_test_group1$p.value > 0.05 & shapiro_test_group2$p.value > 0.05) {
# Perform t-test
t_test_result <- t.test(group1, group2)
print(t_test_result)
} else {
# Perform Wilcoxon rank-sum test
wilcox_test_result <- wilcox.test(group1, group2)
print(wilcox_test_result)
}## Warning in wilcox.test.default(group1, group2): не могу подсчитать точное
## p-значение при наличии повторяющихся наблюдений##
## Wilcoxon rank sum test with continuity correction
##
## data: group1 and group2
## W = 173, p-value = 0.00504
## alternative hypothesis: true location shift is not equal to 0Психоологическое благополучие и место жительства в детстве (значим различия 1\4)
data_list <- list(child_place1$WellBeing, child_place2$WellBeing, child_place3$WellBeing, child_place4$WellBeing)
boxplot(data_list, names = c("Мегаполис", "Город", "Маленький город", "Деревня"), main = "", xlab = "Место жительства в детстве", ylab = "Психологическое благополучие", col = "skyblue", border = "black")
group1 <- child_place1$WellBeing
group2 <- child_place4$WellBeing
# Perform Shapiro-Wilk test for normality
shapiro_test_group1 <- shapiro.test(group1)
shapiro_test_group2 <- shapiro.test(group2)
# Decide which test to use based on the results of normality tests
if (shapiro_test_group1$p.value > 0.05 & shapiro_test_group2$p.value > 0.05) {
# Perform t-test
t_test_result <- t.test(group1, group2)
print(t_test_result)
} else {
# Perform Wilcoxon rank-sum test
wilcox_test_result <- wilcox.test(group1, group2)
print(wilcox_test_result)
}##
## Welch Two Sample t-test
##
## data: group1 and group2
## t = 2.8504, df = 39.071, p-value = 0.006937
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 6.890438 40.558541
## sample estimates:
## mean of x mean of y
## 336.7959 313.0714Создаем таблицу сопряженности и применяем тест хи-квадрат (нет различий)
result <- chisq.test(table(Data$Nationality, Data$Child))
print(result$observed)##
## City Town Village SmallVillage
## France 22 16 14 10
## Russia 27 10 6 4print(result)##
## Pearson's Chi-squared test
##
## data: table(Data$Nationality, Data$Child)
## X-squared = 5.7102, df = 3, p-value = 0.1266регрессия без взаимодейтсвия факторов: идент с природой и благополучие+ценности
model <- lm(EnvIdentity ~ W_PositiveRel + W_Autonomy + W_EnvMastery + W_PersGrowth + W_PurposeLife + W_SelfAcceptance + V_Conformity + V_Tradition + V_Benevolence + V_Universalism + V_Selfdirection + V_Stimulation + V_Hedonism + V_Achievement + V_Power + V_Security + Sex + Adult + Child, data = Data)
final_model <- step(model)## Start: AIC=548.54
## EnvIdentity ~ W_PositiveRel + W_Autonomy + W_EnvMastery + W_PersGrowth +
## W_PurposeLife + W_SelfAcceptance + V_Conformity + V_Tradition +
## V_Benevolence + V_Universalism + V_Selfdirection + V_Stimulation +
## V_Hedonism + V_Achievement + V_Power + V_Security + Sex +
## Adult + Child
##
## Df Sum of Sq RSS AIC
## - Adult 3 72.45 10831 543.27
## - V_Achievement 1 4.85 10763 546.58
## - W_PurposeLife 1 4.88 10763 546.58
## - V_Conformity 1 16.12 10774 546.70
## - W_SelfAcceptance 1 24.62 10783 546.78
## - V_Stimulation 1 31.01 10789 546.85
## - V_Security 1 47.04 10805 547.01
## - W_Autonomy 1 60.03 10818 547.14
## - V_Benevolence 1 65.46 10824 547.20
## - W_EnvMastery 1 81.19 10839 547.35
## - V_Tradition 1 107.97 10866 547.62
## - Sex 1 122.63 10881 547.77
## - W_PositiveRel 1 143.13 10901 547.98
## - V_Hedonism 1 143.46 10902 547.98
## <none> 10758 548.54
## - V_Selfdirection 1 200.50 10959 548.55
## - V_Power 1 274.43 11032 549.28
## - Child 3 770.81 11529 550.08
## - V_Universalism 1 783.59 11542 554.20
## - W_PersGrowth 1 992.12 11750 556.15
##
## Step: AIC=543.27
## EnvIdentity ~ W_PositiveRel + W_Autonomy + W_EnvMastery + W_PersGrowth +
## W_PurposeLife + W_SelfAcceptance + V_Conformity + V_Tradition +
## V_Benevolence + V_Universalism + V_Selfdirection + V_Stimulation +
## V_Hedonism + V_Achievement + V_Power + V_Security + Sex +
## Child
##
## Df Sum of Sq RSS AIC
## - W_PurposeLife 1 2.63 10833 541.29
## - V_Achievement 1 2.69 10833 541.29
## - V_Conformity 1 15.04 10846 541.42
## - W_SelfAcceptance 1 16.26 10847 541.43
## - V_Stimulation 1 32.15 10863 541.59
## - V_Security 1 39.82 10870 541.67
## - V_Benevolence 1 59.75 10890 541.87
## - W_Autonomy 1 63.08 10894 541.90
## - W_EnvMastery 1 100.32 10931 542.27
## - Sex 1 122.07 10953 542.49
## - V_Tradition 1 127.40 10958 542.54
## - W_PositiveRel 1 137.75 10968 542.64
## - V_Hedonism 1 139.49 10970 542.66
## - V_Selfdirection 1 174.26 11005 543.01
## <none> 10831 543.27
## - V_Power 1 268.22 11099 543.93
## - Child 3 872.17 11703 545.71
## - V_Universalism 1 789.06 11620 548.93
## - W_PersGrowth 1 1003.12 11834 550.92
##
## Step: AIC=541.29
## EnvIdentity ~ W_PositiveRel + W_Autonomy + W_EnvMastery + W_PersGrowth +
## W_SelfAcceptance + V_Conformity + V_Tradition + V_Benevolence +
## V_Universalism + V_Selfdirection + V_Stimulation + V_Hedonism +
## V_Achievement + V_Power + V_Security + Sex + Child
##
## Df Sum of Sq RSS AIC
## - V_Achievement 1 1.22 10834 539.31
## - W_SelfAcceptance 1 14.17 10847 539.44
## - V_Conformity 1 21.01 10854 539.50
## - V_Stimulation 1 34.10 10867 539.64
## - V_Security 1 37.44 10871 539.67
## - W_Autonomy 1 60.73 10894 539.90
## - V_Benevolence 1 68.90 10902 539.98
## - W_EnvMastery 1 112.33 10946 540.42
## - Sex 1 119.58 10953 540.49
## - V_Tradition 1 124.85 10958 540.54
## - W_PositiveRel 1 161.63 10995 540.91
## - V_Hedonism 1 168.49 11002 540.98
## <none> 10833 541.29
## - V_Selfdirection 1 205.10 11038 541.34
## - V_Power 1 266.76 11100 541.94
## - Child 3 875.49 11709 543.76
## - V_Universalism 1 800.86 11634 547.07
## - W_PersGrowth 1 1047.28 11880 549.35
##
## Step: AIC=539.31
## EnvIdentity ~ W_PositiveRel + W_Autonomy + W_EnvMastery + W_PersGrowth +
## W_SelfAcceptance + V_Conformity + V_Tradition + V_Benevolence +
## V_Universalism + V_Selfdirection + V_Stimulation + V_Hedonism +
## V_Power + V_Security + Sex + Child
##
## Df Sum of Sq RSS AIC
## - W_SelfAcceptance 1 13.76 10848 537.44
## - V_Conformity 1 24.16 10859 537.55
## - V_Stimulation 1 33.04 10868 537.64
## - V_Security 1 37.16 10872 537.68
## - W_Autonomy 1 60.67 10895 537.91
## - V_Benevolence 1 77.38 10912 538.08
## - W_EnvMastery 1 111.36 10946 538.42
## - Sex 1 118.97 10953 538.50
## - V_Tradition 1 123.90 10958 538.55
## - W_PositiveRel 1 160.47 10995 538.91
## - V_Hedonism 1 180.28 11015 539.10
## <none> 10834 539.31
## - V_Selfdirection 1 208.79 11043 539.39
## - V_Power 1 296.09 11130 540.24
## - Child 3 880.34 11715 541.82
## - V_Universalism 1 808.99 11643 545.16
## - W_PersGrowth 1 1046.93 11881 547.36
##
## Step: AIC=537.44
## EnvIdentity ~ W_PositiveRel + W_Autonomy + W_EnvMastery + W_PersGrowth +
## V_Conformity + V_Tradition + V_Benevolence + V_Universalism +
## V_Selfdirection + V_Stimulation + V_Hedonism + V_Power +
## V_Security + Sex + Child
##
## Df Sum of Sq RSS AIC
## - V_Conformity 1 19.00 10867 535.63
## - V_Stimulation 1 27.84 10876 535.72
## - V_Security 1 47.31 10896 535.92
## - W_Autonomy 1 59.26 10907 536.04
## - V_Benevolence 1 85.48 10934 536.30
## - W_EnvMastery 1 97.63 10946 536.42
## - Sex 1 113.03 10961 536.57
## - V_Tradition 1 130.49 10979 536.75
## - W_PositiveRel 1 148.89 10997 536.93
## - V_Hedonism 1 168.20 11016 537.12
## - V_Selfdirection 1 195.17 11043 537.39
## <none> 10848 537.44
## - V_Power 1 293.47 11142 538.35
## - Child 3 880.63 11729 539.95
## - V_Universalism 1 831.56 11680 543.49
## - W_PersGrowth 1 1063.30 11912 545.64
##
## Step: AIC=535.63
## EnvIdentity ~ W_PositiveRel + W_Autonomy + W_EnvMastery + W_PersGrowth +
## V_Tradition + V_Benevolence + V_Universalism + V_Selfdirection +
## V_Stimulation + V_Hedonism + V_Power + V_Security + Sex +
## Child
##
## Df Sum of Sq RSS AIC
## - V_Stimulation 1 37.21 10904 534.01
## - W_Autonomy 1 51.65 10919 534.15
## - V_Security 1 80.68 10948 534.44
## - W_EnvMastery 1 90.01 10957 534.53
## - Sex 1 119.52 10987 534.83
## - V_Benevolence 1 121.99 10989 534.85
## - W_PositiveRel 1 139.19 11006 535.02
## - V_Hedonism 1 160.63 11028 535.23
## - V_Selfdirection 1 187.37 11054 535.50
## <none> 10867 535.63
## - V_Tradition 1 217.30 11084 535.79
## - V_Power 1 274.64 11142 536.36
## - Child 3 882.25 11749 538.14
## - V_Universalism 1 838.47 11706 541.74
## - W_PersGrowth 1 1046.64 11914 543.66
##
## Step: AIC=534.01
## EnvIdentity ~ W_PositiveRel + W_Autonomy + W_EnvMastery + W_PersGrowth +
## V_Tradition + V_Benevolence + V_Universalism + V_Selfdirection +
## V_Hedonism + V_Power + V_Security + Sex + Child
##
## Df Sum of Sq RSS AIC
## - W_Autonomy 1 44.62 10949 532.45
## - W_EnvMastery 1 65.24 10970 532.66
## - V_Security 1 79.26 10984 532.80
## - V_Benevolence 1 111.21 11016 533.11
## - Sex 1 137.24 11042 533.37
## - V_Hedonism 1 141.96 11046 533.42
## - W_PositiveRel 1 167.92 11072 533.67
## <none> 10904 534.01
## - V_Tradition 1 213.40 11118 534.12
## - V_Selfdirection 1 214.33 11119 534.13
## - V_Power 1 394.69 11299 535.88
## - Child 3 900.65 11805 536.66
## - V_Universalism 1 817.00 11721 539.88
## - W_PersGrowth 1 1014.92 11919 541.71
##
## Step: AIC=532.45
## EnvIdentity ~ W_PositiveRel + W_EnvMastery + W_PersGrowth + V_Tradition +
## V_Benevolence + V_Universalism + V_Selfdirection + V_Hedonism +
## V_Power + V_Security + Sex + Child
##
## Df Sum of Sq RSS AIC
## - V_Security 1 88.40 11037 531.33
## - W_EnvMastery 1 103.73 11053 531.48
## - V_Benevolence 1 118.44 11067 531.63
## - V_Hedonism 1 159.19 11108 532.03
## - W_PositiveRel 1 184.31 11133 532.27
## <none> 10949 532.45
## - V_Tradition 1 204.23 11153 532.47
## - V_Selfdirection 1 211.96 11161 532.54
## - Sex 1 222.11 11171 532.64
## - V_Power 1 415.07 11364 534.51
## - Child 3 1003.07 11952 536.01
## - V_Universalism 1 783.93 11733 537.99
## - W_PersGrowth 1 980.39 11929 539.80
##
## Step: AIC=531.33
## EnvIdentity ~ W_PositiveRel + W_EnvMastery + W_PersGrowth + V_Tradition +
## V_Benevolence + V_Universalism + V_Selfdirection + V_Hedonism +
## V_Power + Sex + Child
##
## Df Sum of Sq RSS AIC
## - W_EnvMastery 1 118.48 11156 530.49
## - V_Benevolence 1 131.46 11169 530.62
## - W_PositiveRel 1 174.12 11212 531.04
## - V_Selfdirection 1 188.96 11226 531.18
## <none> 11037 531.33
## - Sex 1 205.86 11243 531.34
## - V_Hedonism 1 237.58 11275 531.65
## - V_Tradition 1 255.50 11293 531.82
## - V_Power 1 340.65 11378 532.64
## - Child 3 1084.40 12122 535.54
## - V_Universalism 1 887.45 11925 537.76
## - W_PersGrowth 1 1003.53 12041 538.81
##
## Step: AIC=530.49
## EnvIdentity ~ W_PositiveRel + W_PersGrowth + V_Tradition + V_Benevolence +
## V_Universalism + V_Selfdirection + V_Hedonism + V_Power +
## Sex + Child
##
## Df Sum of Sq RSS AIC
## - V_Benevolence 1 112.78 11269 529.59
## - V_Selfdirection 1 145.22 11301 529.90
## - Sex 1 188.57 11344 530.32
## <none> 11156 530.49
## - V_Tradition 1 211.03 11367 530.54
## - W_PositiveRel 1 241.97 11398 530.83
## - V_Hedonism 1 248.77 11405 530.90
## - V_Power 1 353.76 11510 531.90
## - Child 3 1114.80 12271 534.87
## - W_PersGrowth 1 1026.29 12182 538.09
## - V_Universalism 1 1077.22 12233 538.54
##
## Step: AIC=529.59
## EnvIdentity ~ W_PositiveRel + W_PersGrowth + V_Tradition + V_Universalism +
## V_Selfdirection + V_Hedonism + V_Power + Sex + Child
##
## Df Sum of Sq RSS AIC
## - V_Selfdirection 1 91.75 11360 528.47
## - W_PositiveRel 1 191.34 11460 529.42
## <none> 11269 529.59
## - Sex 1 229.70 11498 529.79
## - V_Hedonism 1 302.03 11571 530.47
## - V_Tradition 1 359.12 11628 531.01
## - V_Power 1 388.26 11657 531.28
## - Child 3 1166.88 12436 534.33
## - W_PersGrowth 1 1001.16 12270 536.87
## - V_Universalism 1 1322.27 12591 539.68
##
## Step: AIC=528.47
## EnvIdentity ~ W_PositiveRel + W_PersGrowth + V_Tradition + V_Universalism +
## V_Hedonism + V_Power + Sex + Child
##
## Df Sum of Sq RSS AIC
## - W_PositiveRel 1 195.00 11555 528.33
## <none> 11360 528.47
## - V_Hedonism 1 236.46 11597 528.72
## - V_Tradition 1 308.34 11669 529.39
## - Sex 1 314.74 11675 529.45
## - V_Power 1 439.96 11800 530.61
## - Child 3 1200.76 12561 533.43
## - W_PersGrowth 1 923.14 12284 534.99
## - V_Universalism 1 1320.20 12681 538.46
##
## Step: AIC=528.33
## EnvIdentity ~ W_PersGrowth + V_Tradition + V_Universalism + V_Hedonism +
## V_Power + Sex + Child
##
## Df Sum of Sq RSS AIC
## - V_Hedonism 1 191.06 11746 528.12
## <none> 11555 528.33
## - V_Tradition 1 336.51 11892 529.46
## - Sex 1 350.27 11906 529.58
## - V_Power 1 357.90 11913 529.65
## - W_PersGrowth 1 730.53 12286 533.01
## - Child 3 1217.75 12773 533.25
## - V_Universalism 1 1141.21 12697 536.59
##
## Step: AIC=528.12
## EnvIdentity ~ W_PersGrowth + V_Tradition + V_Universalism + V_Power +
## Sex + Child
##
## Df Sum of Sq RSS AIC
## - V_Power 1 217.00 11964 528.11
## <none> 11746 528.12
## - V_Tradition 1 248.28 11995 528.40
## - Sex 1 321.68 12068 529.06
## - W_PersGrowth 1 598.35 12345 531.53
## - Child 3 1226.41 12973 532.94
## - V_Universalism 1 1518.27 13265 539.37
##
## Step: AIC=528.11
## EnvIdentity ~ W_PersGrowth + V_Tradition + V_Universalism + Sex +
## Child
##
## Df Sum of Sq RSS AIC
## - V_Tradition 1 120.52 12084 527.20
## <none> 11964 528.11
## - Sex 1 279.36 12243 528.63
## - W_PersGrowth 1 543.82 12507 530.96
## - Child 3 1236.96 13200 532.84
## - V_Universalism 1 1815.56 13779 541.51
##
## Step: AIC=527.2
## EnvIdentity ~ W_PersGrowth + V_Universalism + Sex + Child
##
## Df Sum of Sq RSS AIC
## <none> 12084 527.20
## - Sex 1 293.96 12378 527.82
## - W_PersGrowth 1 440.59 12525 529.11
## - Child 3 1256.58 13341 531.99
## - V_Universalism 1 2816.30 14900 548.04summary(final_model)##
## Call:
## lm(formula = EnvIdentity ~ W_PersGrowth + V_Universalism + Sex +
## Child, data = Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -27.329 -5.080 1.320 7.012 22.243
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 27.0349 8.8038 3.071 0.00274 **
## W_PersGrowth 0.2257 0.1170 1.928 0.05658 .
## V_Universalism 4.6266 0.9489 4.876 0.000004 ***
## SexMale -3.4475 2.1886 -1.575 0.11830
## Child.L 7.2144 2.3635 3.052 0.00289 **
## Child.Q 2.9718 2.3139 1.284 0.20193
## Child.C -2.4177 2.3335 -1.036 0.30263
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 10.88 on 102 degrees of freedom
## Multiple R-squared: 0.2985, Adjusted R-squared: 0.2572
## F-statistic: 7.233 on 6 and 102 DF, p-value: 0.000001888регрессия со взаимодейтсвием факторов: идент с природой и благополучие+ценности : национальность
model <- lm(EnvIdentity ~ (W_PositiveRel + W_Autonomy + W_EnvMastery + W_PersGrowth + W_PurposeLife + W_SelfAcceptance + V_Conformity + V_Tradition + V_Benevolence + V_Universalism + V_Selfdirection + V_Stimulation + V_Hedonism + V_Achievement + V_Power + V_Security + Sex + Adult + Child) : Nationality, data = Data)
final_model <- step(model)## Start: AIC=552.25
## EnvIdentity ~ (W_PositiveRel + W_Autonomy + W_EnvMastery + W_PersGrowth +
## W_PurposeLife + W_SelfAcceptance + V_Conformity + V_Tradition +
## V_Benevolence + V_Universalism + V_Selfdirection + V_Stimulation +
## V_Hedonism + V_Achievement + V_Power + V_Security + Sex +
## Adult + Child):Nationality
##
## Df Sum of Sq RSS AIC
## - Adult:Nationality 6 434.97 7734.1 546.56
## - V_Tradition:Nationality 2 35.20 7334.3 548.78
## - V_Benevolence:Nationality 2 35.42 7334.5 548.78
## - V_Achievement:Nationality 2 62.94 7362.1 549.19
## - V_Conformity:Nationality 2 64.07 7363.2 549.21
## - W_SelfAcceptance:Nationality 2 71.84 7371.0 549.32
## - V_Stimulation:Nationality 2 73.76 7372.9 549.35
## - W_PositiveRel:Nationality 2 129.88 7429.0 550.18
## - Sex:Nationality 2 159.82 7458.9 550.61
## - W_Autonomy:Nationality 2 178.48 7477.6 550.89
## - V_Selfdirection:Nationality 2 183.32 7482.4 550.96
## - W_PersGrowth:Nationality 2 225.88 7525.0 551.58
## - V_Hedonism:Nationality 2 251.85 7551.0 551.95
## <none> 7299.1 552.25
## - V_Security:Nationality 2 276.72 7575.8 552.31
## - W_PurposeLife:Nationality 2 437.42 7736.5 554.60
## - V_Power:Nationality 2 490.81 7789.9 555.35
## - W_EnvMastery:Nationality 2 550.29 7849.4 556.18
## - V_Universalism:Nationality 2 909.33 8208.4 561.05
## - Child:Nationality 6 1742.28 9041.4 563.59
##
## Step: AIC=546.56
## EnvIdentity ~ W_PositiveRel:Nationality + W_Autonomy:Nationality +
## W_EnvMastery:Nationality + W_PersGrowth:Nationality + W_PurposeLife:Nationality +
## W_SelfAcceptance:Nationality + V_Conformity:Nationality +
## V_Tradition:Nationality + V_Benevolence:Nationality + V_Universalism:Nationality +
## V_Selfdirection:Nationality + V_Stimulation:Nationality +
## V_Hedonism:Nationality + V_Achievement:Nationality + V_Power:Nationality +
## V_Security:Nationality + Sex:Nationality + Child:Nationality
##
## Df Sum of Sq RSS AIC
## - Nationality:V_Tradition 2 20.92 7755.0 542.86
## - Nationality:V_Achievement 2 24.59 7758.7 542.91
## - Nationality:V_Benevolence 2 37.11 7771.2 543.08
## - Nationality:V_Stimulation 2 44.59 7778.7 543.19
## - Nationality:W_SelfAcceptance 2 52.50 7786.6 543.30
## - Nationality:V_Conformity 2 117.08 7851.2 544.20
## - Nationality:Sex 2 152.91 7887.0 544.70
## - W_PositiveRel:Nationality 2 166.36 7900.4 544.88
## - Nationality:V_Hedonism 2 166.57 7900.7 544.89
## - Nationality:V_Selfdirection 2 212.24 7946.3 545.51
## - Nationality:V_Security 2 251.91 7986.0 546.06
## - Nationality:W_PersGrowth 2 265.05 7999.1 546.24
## <none> 7734.1 546.56
## - Nationality:W_PurposeLife 2 390.55 8124.6 547.93
## - Nationality:W_EnvMastery 2 443.83 8177.9 548.65
## - Nationality:W_Autonomy 2 455.14 8189.2 548.80
## - Nationality:V_Power 2 517.14 8251.2 549.62
## - Nationality:V_Universalism 2 938.82 8672.9 555.05
## - Nationality:Child 6 1827.74 9561.8 557.69
##
## Step: AIC=542.86
## EnvIdentity ~ W_PositiveRel:Nationality + Nationality:W_Autonomy +
## Nationality:W_EnvMastery + Nationality:W_PersGrowth + Nationality:W_PurposeLife +
## Nationality:W_SelfAcceptance + Nationality:V_Conformity +
## Nationality:V_Benevolence + Nationality:V_Universalism +
## Nationality:V_Selfdirection + Nationality:V_Stimulation +
## Nationality:V_Hedonism + Nationality:V_Achievement + Nationality:V_Power +
## Nationality:V_Security + Nationality:Sex + Nationality:Child
##
## Df Sum of Sq RSS AIC
## - Nationality:V_Achievement 2 22.45 7777.5 539.17
## - Nationality:V_Benevolence 2 37.26 7792.3 539.38
## - Nationality:V_Stimulation 2 41.43 7796.4 539.44
## - Nationality:W_SelfAcceptance 2 69.94 7824.9 539.84
## - Nationality:Sex 2 172.64 7927.7 541.26
## - Nationality:V_Hedonism 2 183.19 7938.2 541.40
## - W_PositiveRel:Nationality 2 185.84 7940.9 541.44
## - Nationality:V_Conformity 2 199.09 7954.1 541.62
## - Nationality:V_Selfdirection 2 208.24 7963.2 541.75
## - Nationality:W_PersGrowth 2 265.96 8021.0 542.53
## - Nationality:V_Security 2 268.73 8023.7 542.57
## <none> 7755.0 542.86
## - Nationality:W_EnvMastery 2 432.49 8187.5 544.77
## - Nationality:W_PurposeLife 2 458.89 8213.9 545.12
## - Nationality:W_Autonomy 2 465.60 8220.6 545.21
## - Nationality:V_Power 2 508.10 8263.1 545.77
## - Nationality:V_Universalism 2 1042.89 8797.9 552.61
## - Nationality:Child 6 1886.88 9641.9 554.60
##
## Step: AIC=539.17
## EnvIdentity ~ W_PositiveRel:Nationality + Nationality:W_Autonomy +
## Nationality:W_EnvMastery + Nationality:W_PersGrowth + Nationality:W_PurposeLife +
## Nationality:W_SelfAcceptance + Nationality:V_Conformity +
## Nationality:V_Benevolence + Nationality:V_Universalism +
## Nationality:V_Selfdirection + Nationality:V_Stimulation +
## Nationality:V_Hedonism + Nationality:V_Power + Nationality:V_Security +
## Nationality:Sex + Nationality:Child
##
## Df Sum of Sq RSS AIC
## - Nationality:V_Stimulation 2 39.73 7817.2 535.73
## - Nationality:W_SelfAcceptance 2 58.37 7835.8 535.99
## - Nationality:V_Benevolence 2 73.01 7850.5 536.19
## - Nationality:Sex 2 170.40 7947.9 537.53
## - Nationality:V_Hedonism 2 175.56 7953.0 537.61
## - W_PositiveRel:Nationality 2 185.75 7963.2 537.75
## - Nationality:V_Selfdirection 2 207.28 7984.7 538.04
## - Nationality:V_Security 2 247.15 8024.6 538.58
## - Nationality:V_Conformity 2 266.45 8043.9 538.84
## - Nationality:W_PersGrowth 2 268.03 8045.5 538.87
## <none> 7777.5 539.17
## - Nationality:W_EnvMastery 2 433.99 8211.5 541.09
## - Nationality:W_Autonomy 2 480.77 8258.2 541.71
## - Nationality:V_Power 2 509.65 8287.1 542.09
## - Nationality:W_PurposeLife 2 556.16 8333.6 542.70
## - Nationality:V_Universalism 2 1029.31 8806.8 548.72
## - Nationality:Child 6 1872.33 9649.8 550.68
##
## Step: AIC=535.73
## EnvIdentity ~ W_PositiveRel:Nationality + Nationality:W_Autonomy +
## Nationality:W_EnvMastery + Nationality:W_PersGrowth + Nationality:W_PurposeLife +
## Nationality:W_SelfAcceptance + Nationality:V_Conformity +
## Nationality:V_Benevolence + Nationality:V_Universalism +
## Nationality:V_Selfdirection + Nationality:V_Hedonism + Nationality:V_Power +
## Nationality:V_Security + Nationality:Sex + Nationality:Child
##
## Df Sum of Sq RSS AIC
## - Nationality:V_Benevolence 2 56.41 7873.6 532.51
## - Nationality:W_SelfAcceptance 2 73.90 7891.1 532.75
## - Nationality:Sex 2 172.48 7989.7 534.11
## - Nationality:V_Hedonism 2 191.09 8008.3 534.36
## - W_PositiveRel:Nationality 2 207.64 8024.8 534.59
## - Nationality:V_Selfdirection 2 237.69 8054.9 534.99
## - Nationality:W_PersGrowth 2 240.72 8057.9 535.03
## - Nationality:V_Security 2 249.84 8067.0 535.16
## - Nationality:V_Conformity 2 271.50 8088.7 535.45
## <none> 7817.2 535.73
## - Nationality:W_EnvMastery 2 397.43 8214.6 537.13
## - Nationality:W_Autonomy 2 517.18 8334.4 538.71
## - Nationality:W_PurposeLife 2 595.61 8412.8 539.73
## - Nationality:V_Power 2 671.51 8488.7 540.71
## - Nationality:V_Universalism 2 1044.26 8861.4 545.39
## - Nationality:Child 6 1865.58 9682.8 547.06
##
## Step: AIC=532.51
## EnvIdentity ~ W_PositiveRel:Nationality + Nationality:W_Autonomy +
## Nationality:W_EnvMastery + Nationality:W_PersGrowth + Nationality:W_PurposeLife +
## Nationality:W_SelfAcceptance + Nationality:V_Conformity +
## Nationality:V_Universalism + Nationality:V_Selfdirection +
## Nationality:V_Hedonism + Nationality:V_Power + Nationality:V_Security +
## Nationality:Sex + Nationality:Child
##
## Df Sum of Sq RSS AIC
## - Nationality:W_SelfAcceptance 2 142.63 8016.2 530.47
## - Nationality:Sex 2 193.48 8067.1 531.16
## - Nationality:V_Hedonism 2 215.43 8089.0 531.45
## - Nationality:V_Selfdirection 2 241.14 8114.7 531.80
## - Nationality:W_PersGrowth 2 241.27 8114.9 531.80
## - W_PositiveRel:Nationality 2 254.20 8127.8 531.98
## <none> 7873.6 532.51
## - Nationality:V_Conformity 2 302.22 8175.8 532.62
## - Nationality:V_Security 2 335.71 8209.3 533.06
## - Nationality:W_EnvMastery 2 368.27 8241.9 533.49
## - Nationality:W_Autonomy 2 523.38 8397.0 535.53
## - Nationality:W_PurposeLife 2 656.28 8529.9 537.24
## - Nationality:V_Power 2 748.22 8621.8 538.41
## - Nationality:V_Universalism 2 1270.74 9144.3 544.82
## - Nationality:Child 6 2112.76 9986.4 546.42
##
## Step: AIC=530.47
## EnvIdentity ~ W_PositiveRel:Nationality + Nationality:W_Autonomy +
## Nationality:W_EnvMastery + Nationality:W_PersGrowth + Nationality:W_PurposeLife +
## Nationality:V_Conformity + Nationality:V_Universalism + Nationality:V_Selfdirection +
## Nationality:V_Hedonism + Nationality:V_Power + Nationality:V_Security +
## Nationality:Sex + Nationality:Child
##
## Df Sum of Sq RSS AIC
## - Nationality:V_Hedonism 2 177.56 8193.8 528.86
## - Nationality:W_PersGrowth 2 180.17 8196.4 528.89
## - Nationality:Sex 2 201.01 8217.2 529.17
## - W_PositiveRel:Nationality 2 215.28 8231.5 529.36
## - Nationality:V_Selfdirection 2 236.97 8253.2 529.64
## <none> 8016.2 530.47
## - Nationality:V_Conformity 2 320.03 8336.3 530.74
## - Nationality:V_Security 2 343.35 8359.6 531.04
## - Nationality:W_EnvMastery 2 391.17 8407.4 531.66
## - Nationality:W_PurposeLife 2 552.23 8568.5 533.73
## - Nationality:W_Autonomy 2 565.01 8581.2 533.89
## - Nationality:V_Power 2 842.19 8858.4 537.36
## - Nationality:V_Universalism 2 1274.57 9290.8 542.55
## - Nationality:Child 6 2163.16 10179.4 544.51
##
## Step: AIC=528.86
## EnvIdentity ~ W_PositiveRel:Nationality + Nationality:W_Autonomy +
## Nationality:W_EnvMastery + Nationality:W_PersGrowth + Nationality:W_PurposeLife +
## Nationality:V_Conformity + Nationality:V_Universalism + Nationality:V_Selfdirection +
## Nationality:V_Power + Nationality:V_Security + Nationality:Sex +
## Nationality:Child
##
## Df Sum of Sq RSS AIC
## - Nationality:W_PersGrowth 2 133.04 8326.8 526.61
## - W_PositiveRel:Nationality 2 135.30 8329.1 526.64
## - Nationality:V_Selfdirection 2 179.88 8373.7 527.22
## - Nationality:Sex 2 245.38 8439.2 528.07
## - Nationality:V_Security 2 281.12 8474.9 528.53
## <none> 8193.8 528.86
## - Nationality:V_Conformity 2 386.94 8580.7 529.89
## - Nationality:W_EnvMastery 2 405.40 8599.2 530.12
## - Nationality:W_PurposeLife 2 464.90 8658.7 530.87
## - Nationality:W_Autonomy 2 657.14 8850.9 533.27
## - Nationality:V_Power 2 1038.81 9232.6 537.87
## - Nationality:V_Universalism 2 1176.46 9370.3 539.48
## - Nationality:Child 6 2088.33 10282.1 541.60
##
## Step: AIC=526.61
## EnvIdentity ~ W_PositiveRel:Nationality + Nationality:W_Autonomy +
## Nationality:W_EnvMastery + Nationality:W_PurposeLife + Nationality:V_Conformity +
## Nationality:V_Universalism + Nationality:V_Selfdirection +
## Nationality:V_Power + Nationality:V_Security + Nationality:Sex +
## Nationality:Child
##
## Df Sum of Sq RSS AIC
## - W_PositiveRel:Nationality 2 105.18 8432.0 523.98
## - Nationality:V_Selfdirection 2 130.62 8457.5 524.31
## - Nationality:V_Security 2 262.41 8589.2 525.99
## <none> 8326.8 526.61
## - Nationality:Sex 2 318.67 8645.5 526.71
## - Nationality:W_EnvMastery 2 331.76 8658.6 526.87
## - Nationality:V_Conformity 2 355.05 8681.9 527.16
## - Nationality:W_PurposeLife 2 572.28 8899.1 529.86
## - Nationality:W_Autonomy 2 683.02 9009.8 531.21
## - Nationality:V_Power 2 1047.43 9374.3 535.53
## - Nationality:V_Universalism 2 1286.21 9613.0 538.27
## - Nationality:Child 6 2086.23 10413.1 538.98
##
## Step: AIC=523.98
## EnvIdentity ~ Nationality:W_Autonomy + Nationality:W_EnvMastery +
## Nationality:W_PurposeLife + Nationality:V_Conformity + Nationality:V_Universalism +
## Nationality:V_Selfdirection + Nationality:V_Power + Nationality:V_Security +
## Nationality:Sex + Nationality:Child
##
## Df Sum of Sq RSS AIC
## - Nationality:V_Selfdirection 2 115.84 8547.9 521.47
## - Nationality:V_Security 2 310.36 8742.4 523.92
## <none> 8432.0 523.98
## - Nationality:W_EnvMastery 2 315.60 8747.6 523.99
## - Nationality:Sex 2 360.27 8792.3 524.54
## - Nationality:V_Conformity 2 366.17 8798.2 524.61
## - Nationality:W_Autonomy 2 635.28 9067.3 527.90
## - Nationality:W_PurposeLife 2 781.48 9213.5 529.64
## - Nationality:V_Power 2 1011.85 9443.9 532.33
## - Nationality:V_Universalism 2 1183.65 9615.7 534.30
## - Nationality:Child 6 1983.02 10415.0 535.00
##
## Step: AIC=521.47
## EnvIdentity ~ Nationality:W_Autonomy + Nationality:W_EnvMastery +
## Nationality:W_PurposeLife + Nationality:V_Conformity + Nationality:V_Universalism +
## Nationality:V_Power + Nationality:V_Security + Nationality:Sex +
## Nationality:Child
##
## Df Sum of Sq RSS AIC
## - Nationality:W_EnvMastery 2 246.40 8794.3 520.57
## - Nationality:V_Security 2 294.57 8842.4 521.16
## - Nationality:V_Conformity 2 306.96 8854.8 521.31
## <none> 8547.9 521.47
## - Nationality:Sex 2 351.32 8899.2 521.86
## - Nationality:W_Autonomy 2 662.13 9210.0 525.60
## - Nationality:W_PurposeLife 2 850.50 9398.4 527.81
## - Nationality:V_Power 2 1047.43 9595.3 530.07
## - Nationality:V_Universalism 2 1150.89 9698.8 531.24
## - Nationality:Child 6 1997.76 10545.6 532.36
##
## Step: AIC=520.57
## EnvIdentity ~ Nationality:W_Autonomy + Nationality:W_PurposeLife +
## Nationality:V_Conformity + Nationality:V_Universalism + Nationality:V_Power +
## Nationality:V_Security + Nationality:Sex + Nationality:Child
##
## Df Sum of Sq RSS AIC
## - Nationality:V_Conformity 2 190.96 8985.2 518.91
## <none> 8794.3 520.57
## - Nationality:Sex 2 395.08 9189.3 521.36
## - Nationality:V_Security 2 425.89 9220.2 521.72
## - Nationality:W_Autonomy 2 927.10 9721.4 527.49
## - Nationality:W_PurposeLife 2 988.00 9782.3 528.17
## - Nationality:V_Power 2 988.49 9782.8 528.18
## - Nationality:Child 6 1831.59 10625.9 529.19
## - Nationality:V_Universalism 2 1514.92 10309.2 533.89
##
## Step: AIC=518.91
## EnvIdentity ~ Nationality:W_Autonomy + Nationality:W_PurposeLife +
## Nationality:V_Universalism + Nationality:V_Power + Nationality:V_Security +
## Nationality:Sex + Nationality:Child
##
## Df Sum of Sq RSS AIC
## <none> 8985.2 518.91
## - Nationality:Sex 2 534.91 9520.1 521.21
## - Nationality:V_Security 2 749.21 9734.4 523.64
## - Nationality:V_Power 2 805.89 9791.1 524.27
## - Nationality:W_PurposeLife 2 997.79 9983.0 526.38
## - Nationality:W_Autonomy 2 1012.41 9997.6 526.54
## - Nationality:Child 6 1955.40 10940.6 528.37
## - Nationality:V_Universalism 2 1963.33 10948.6 536.45summary(final_model)##
## Call:
## lm(formula = EnvIdentity ~ Nationality:W_Autonomy + Nationality:W_PurposeLife +
## Nationality:V_Universalism + Nationality:V_Power + Nationality:V_Security +
## Nationality:Sex + Nationality:Child, data = Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -33.091 -5.275 0.575 5.377 21.100
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 37.9153 10.9783 3.454 0.000845 ***
## NationalityFrance:W_Autonomy 0.2651 0.2276 1.165 0.247286
## NationalityRussia:W_Autonomy -0.5604 0.2220 -2.524 0.013350 *
## NationalityFrance:W_PurposeLife -0.3279 0.1356 -2.419 0.017576 *
## NationalityRussia:W_PurposeLife 0.3264 0.1802 1.811 0.073484 .
## NationalityFrance:V_Universalism 5.3152 1.3698 3.880 0.000198 ***
## NationalityRussia:V_Universalism 3.8468 1.7947 2.143 0.034777 *
## NationalityFrance:V_Power -2.9950 1.0625 -2.819 0.005928 **
## NationalityRussia:V_Power -0.2996 0.9629 -0.311 0.756421
## NationalityFrance:V_Security 2.5048 1.2006 2.086 0.039786 *
## NationalityRussia:V_Security 3.7604 2.0289 1.853 0.067105 .
## NationalityFrance:SexMale -4.7662 2.7736 -1.718 0.089161 .
## NationalityRussia:SexMale 6.0312 3.8881 1.551 0.124365
## NationalityFrance:Child.L 8.7384 2.7569 3.170 0.002086 **
## NationalityRussia:Child.L 0.6367 4.2152 0.151 0.880267
## NationalityFrance:Child.Q 1.4220 2.7136 0.524 0.601554
## NationalityRussia:Child.Q 1.9483 3.9809 0.489 0.625740
## NationalityFrance:Child.C -6.7528 2.6507 -2.548 0.012545 *
## NationalityRussia:Child.C 6.3439 3.8490 1.648 0.102806
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 9.992 on 90 degrees of freedom
## Multiple R-squared: 0.4784, Adjusted R-squared: 0.3741
## F-statistic: 4.586 on 18 and 90 DF, p-value: 0.0000005687