exploratory
Jiner Zheng
2022-04-19
Variables from Prosperity Index
persfreedomagency: Pillar of Personal Freedom –> the degree to which citizens are free from restriction and are free to move, indicating the experiences of the freedom to act independently and making free choices
- its indicators consist of e.g. personal autonomy and individual rights, freedom of movement, satisfaction with freedom, etc.)
Socialcapsocialnetwork: Social network (pillar of Social capital)
- the strength and opportunities of the individuals’ relationships with wider social network, including social support (e.g. respect, opportunity to make friends or helping another household)
Healthprevent: Preventative interventions (pillar of Health)
- the extent to which the health system prevents diseases and other medical complications from occurring (e.g. the existence of national screening programs, or diphteria, measles, hepatitis immunization, etc.)
Socialcapcivic: Civic and social participation (pillar of Social capital)
- the amount to which citizens participate within the society, split into the civic and social spheres (e.g. donated money to charity, volunteering, etc.)
PersonalFreedom: Freedom of assembly and association (pillar of Personal Freedom)
- the degree to which citizens have the freedom to assemble with others in public spaces, or to express their opinions
GovernanGovernmeffect: Government effectiveness (pillar of Governance)
- the quality of public health provision, the competence of officials and the quality of the bureaucracy (e.g. policy coordination, government quality and credibility, efficiency of government spending, etc.)
Socialcappersonalandfamily: Personal and family relationships (pillar of Social capital)
- the strength of the closest personal relationships and family ties, forming the individual’s emotional, mental and financial support (e.g. help from family and friends when in trouble or the positive energy provided by the family)
Clustering using gower distance
Pick number of clusters using the silhouette figure
2 clusters has the highest silhouette width. 3 is simpler and almost as good. Let’s pick k = 3
Interpretation
Summary of each cluster
## [[1]]
## location stringency_class excess_death_class persfreedomagency
## Length:28 1: 7 1:23 Min. : 9.40
## Class :character 2:14 2: 1 1st Qu.:15.97
## Mode :character 3: 6 3: 2 Median :17.80
## 4: 1 4: 2 Mean :17.66
## 3rd Qu.:19.60
## Max. :22.40
## Socialcapsocialnetwork healthprevent Socialcapcivic PersonalFreedom
## Min. : 5.10 Min. : 9.20 Min. : 4.100 Min. : 5.40
## 1st Qu.:12.28 1st Qu.:12.32 1st Qu.: 4.825 1st Qu.:12.97
## Median :13.25 Median :13.05 Median : 6.000 Median :15.85
## Mean :13.12 Mean :12.77 Mean : 6.743 Mean :14.97
## 3rd Qu.:14.60 3rd Qu.:13.60 3rd Qu.: 8.100 3rd Qu.:17.30
## Max. :16.00 Max. :14.00 Max. :12.200 Max. :18.80
## GovernanGovernmeffect Socialcappersonalandfamily population
## Min. : 5.90 Min. :10.60 Min. : 98910
## 1st Qu.:11.25 1st Qu.:15.07 1st Qu.: 3165828
## Median :13.50 Median :16.05 Median : 6820349
## Mean :13.28 Mean :15.46 Mean : 25975695
## 3rd Qu.:15.03 3rd Qu.:16.32 3rd Qu.: 9906760
## Max. :19.10 Max. :17.30 Max. :332915074
## population_density median_age aged_65_older gdp_per_capita
## Min. : 8.823 Min. :30.60 Min. : 8.514 Min. : 5190
## 1st Qu.: 60.058 1st Qu.:37.90 1st Qu.:13.931 1st Qu.:19860
## Median : 103.745 Median :42.15 Median :16.666 Median :25723
## Mean : 387.224 Mean :40.66 Mean :16.072 Mean :27103
## 3rd Qu.: 154.347 3rd Qu.:43.60 3rd Qu.:19.036 3rd Qu.:31702
## Max. :7039.714 Max. :47.90 Max. :23.021 Max. :57410
## life_expectancy Climateclass
## Min. :71.90 : 0
## 1st Qu.:75.77 Class A - Tropical Climates : 3
## Median :78.20 Class B - Dry (Arid and Semiarid) Climates : 1
## Mean :78.02 Class C - Temperate (Mesothermal) Climates :21
## 3rd Qu.:79.58 Class D - Continental (Microthermal) Climates: 3
## Max. :84.86
## cluster
## Min. :1
## 1st Qu.:1
## Median :1
## Mean :1
## 3rd Qu.:1
## Max. :1
##
## [[2]]
## location stringency_class excess_death_class persfreedomagency
## Length:21 1:7 1: 2 Min. :16.1
## Class :character 2:5 2: 1 1st Qu.:20.8
## Mode :character 3:6 3:12 Median :21.6
## 4:3 4: 6 Mean :20.9
## 3rd Qu.:21.9
## Max. :23.8
## Socialcapsocialnetwork healthprevent Socialcapcivic PersonalFreedom
## Min. : 8.00 Min. :12.90 Min. : 4.10 Min. : 7.20
## 1st Qu.:14.00 1st Qu.:13.30 1st Qu.: 6.90 1st Qu.:17.70
## Median :15.10 Median :13.60 Median : 9.80 Median :18.20
## Mean :14.41 Mean :13.57 Mean : 9.51 Mean :17.58
## 3rd Qu.:15.70 3rd Qu.:13.90 3rd Qu.:12.40 3rd Qu.:18.50
## Max. :16.40 Max. :14.10 Max. :14.00 Max. :19.50
## GovernanGovernmeffect Socialcappersonalandfamily population
## Min. :12.10 Min. :12.10 Min. : 368792
## 1st Qu.:17.70 1st Qu.:15.70 1st Qu.: 5126300
## Median :18.20 Median :16.20 Median : 10160159
## Mean :17.47 Mean :16.13 Mean : 23633669
## 3rd Qu.:18.70 3rd Qu.:17.10 3rd Qu.: 25788217
## Max. :18.90 Max. :18.30 Max. :126050796
## population_density median_age aged_65_older gdp_per_capita
## Min. : 3.202 Min. :37.30 Min. :12.92 Min. :24574
## 1st Qu.: 24.718 1st Qu.:39.70 1st Qu.:14.43 1st Qu.:36086
## Median : 127.657 Median :42.30 Median :18.57 Median :42659
## Mean : 598.863 Mean :41.92 Mean :17.93 Mean :46674
## 3rd Qu.: 347.778 3rd Qu.:43.40 3rd Qu.:19.98 3rd Qu.:46949
## Max. :7915.731 Max. :48.20 Max. :27.05 Max. :94278
## life_expectancy Climateclass
## Min. :80.90 : 0
## 1st Qu.:81.91 Class A - Tropical Climates : 1
## Median :82.29 Class B - Dry (Arid and Semiarid) Climates : 1
## Mean :82.40 Class C - Temperate (Mesothermal) Climates :16
## 3rd Qu.:82.99 Class D - Continental (Microthermal) Climates: 3
## Max. :84.63
## cluster
## Min. :2
## 1st Qu.:2
## Median :2
## Mean :2
## 3rd Qu.:2
## Max. :2
##
## [[3]]
## location stringency_class excess_death_class persfreedomagency
## Length:21 1:13 1: 2 Min. : 5.70
## Class :character 2: 1 2:14 1st Qu.:12.20
## Mode :character 3: 6 3: 2 Median :14.70
## 4: 1 4: 3 Mean :13.51
## 3rd Qu.:15.60
## Max. :20.00
## Socialcapsocialnetwork healthprevent Socialcapcivic PersonalFreedom
## Min. :10.10 Min. : 9.60 Min. : 0.800 Min. : 1.7
## 1st Qu.:13.60 1st Qu.:11.60 1st Qu.: 4.100 1st Qu.: 3.7
## Median :14.90 Median :12.70 Median : 5.700 Median :12.1
## Mean :14.28 Mean :12.61 Mean : 5.952 Mean : 9.7
## 3rd Qu.:15.50 3rd Qu.:13.70 3rd Qu.: 8.200 3rd Qu.:13.5
## Max. :16.30 Max. :14.40 Max. :10.700 Max. :17.5
## GovernanGovernmeffect Socialcappersonalandfamily population
## Min. : 5.200 Min. : 9.70 Min. : 2930524
## 1st Qu.: 8.000 1st Qu.:14.50 1st Qu.: 7219641
## Median : 9.400 Median :15.40 Median : 18994958
## Mean : 9.343 Mean :15.06 Mean : 44439202
## 3rd Qu.:10.300 3rd Qu.:16.50 3rd Qu.: 60041996
## Max. :12.500 Max. :18.00 Max. :213993441
## population_density median_age aged_65_older gdp_per_capita
## Min. : 1.98 Min. :22.90 Min. : 1.307 Min. : 3393
## 1st Qu.: 25.04 1st Qu.:27.30 1st Qu.: 4.694 1st Qu.: 8827
## Median : 49.83 Median :29.30 Median : 6.378 Median : 12295
## Mean : 66.42 Mean :30.28 Mean : 6.571 Mean : 18503
## 3rd Qu.: 96.08 3rd Qu.:32.40 3rd Qu.: 7.151 3rd Qu.: 16278
## Max. :227.32 Max. :41.40 Max. :16.462 Max. :116936
## life_expectancy Climateclass
## Min. :64.13 :0
## 1st Qu.:71.99 Class A - Tropical Climates :8
## Median :74.30 Class B - Dry (Arid and Semiarid) Climates :8
## Mean :74.38 Class C - Temperate (Mesothermal) Climates :2
## 3rd Qu.:77.01 Class D - Continental (Microthermal) Climates:3
## Max. :80.28
## cluster
## Min. :3
## 1st Qu.:3
## Median :3
## Mean :3
## 3rd Qu.:3
## Max. :3Cluster 1: 19 Countries
| location | excess_death_class | stringency_class | Climateclass |
|---|---|---|---|
| Albania | 1 | 1 | Class C - Temperate (Mesothermal) Climates |
| Austria | 1 | 2 | Class C - Temperate (Mesothermal) Climates |
| Bosnia and Herzegovina | 1 | 1 | Class C - Temperate (Mesothermal) Climates |
| Bulgaria | 1 | 2 | Class C - Temperate (Mesothermal) Climates |
| Croatia | 1 | 1 | Class C - Temperate (Mesothermal) Climates |
| Czechia | 1 | 2 | Class C - Temperate (Mesothermal) Climates |
| Estonia | 1 | 1 | Class D - Continental (Microthermal) Climates |
| Georgia | 1 | 2 | Class C - Temperate (Mesothermal) Climates |
| Hungary | 1 | 3 | Class C - Temperate (Mesothermal) Climates |
| Israel | 1 | 2 | Class C - Temperate (Mesothermal) Climates |
| Latvia | 1 | 1 | Class C - Temperate (Mesothermal) Climates |
| Lebanon | 1 | 3 | Class C - Temperate (Mesothermal) Climates |
| Lithuania | 1 | 2 | Class D - Continental (Microthermal) Climates |
| Moldova | 1 | 3 | Class C - Temperate (Mesothermal) Climates |
| Poland | 1 | 2 | Class C - Temperate (Mesothermal) Climates |
| Russia | 1 | 1 | Class D - Continental (Microthermal) Climates |
| Serbia | 1 | 1 | Class C - Temperate (Mesothermal) Climates |
| Seychelles | 1 | 4 | Class A - Tropical Climates |
| Slovakia | 1 | 2 | Class C - Temperate (Mesothermal) Climates |
| Slovenia | 1 | 2 | Class C - Temperate (Mesothermal) Climates |
| Switzerland | 1 | 2 | Class C - Temperate (Mesothermal) Climates |
| United States | 1 | 3 | Class C - Temperate (Mesothermal) Climates |
| Uruguay | 1 | 3 | Class C - Temperate (Mesothermal) Climates |
| Romania | 2 | 2 | Class C - Temperate (Mesothermal) Climates |
| Hong Kong | 3 | 2 | Class A - Tropical Climates |
| Mauritius | 3 | 2 | Class A - Tropical Climates |
| Chile | 4 | 3 | Class B - Dry (Arid and Semiarid) Climates |
| Italy | 4 | 2 | Class C - Temperate (Mesothermal) Climates |
|
|
|
Cluster 1 countries profile – other variables
58% (11/19 countries) in Excess Death Class 4 (e.g. Russia, Hungary, Ukraine)
63% (12/19 countries) in Stringency Class 1
68% (13/19 countries) in Temperate (Mesothermal) Climates
Cluster 2: 27 Countries
| location | excess_death_class | stringency_class | Climateclass |
|---|---|---|---|
| Luxembourg | 1 | 1 | Class C - Temperate (Mesothermal) Climates |
| Malta | 1 | 1 | Class C - Temperate (Mesothermal) Climates |
| Portugal | 2 | 3 | Class C - Temperate (Mesothermal) Climates |
| Australia | 3 | 2 | Class B - Dry (Arid and Semiarid) Climates |
| Cyprus | 3 | 1 | Class C - Temperate (Mesothermal) Climates |
| Denmark | 3 | 2 | Class C - Temperate (Mesothermal) Climates |
| Finland | 3 | 1 | Class D - Continental (Microthermal) Climates |
| Germany | 3 | 4 | Class C - Temperate (Mesothermal) Climates |
| Greece | 3 | 4 | Class C - Temperate (Mesothermal) Climates |
| Iceland | 3 | 2 | Class C - Temperate (Mesothermal) Climates |
| Japan | 3 | 4 | Class C - Temperate (Mesothermal) Climates |
| New Zealand | 3 | 1 | Class C - Temperate (Mesothermal) Climates |
| Norway | 3 | 3 | Class D - Continental (Microthermal) Climates |
| Singapore | 3 | 1 | Class A - Tropical Climates |
| South Korea | 3 | 3 | Class C - Temperate (Mesothermal) Climates |
| Belgium | 4 | 1 | Class C - Temperate (Mesothermal) Climates |
| Ireland | 4 | 2 | Class C - Temperate (Mesothermal) Climates |
| Netherlands | 4 | 2 | Class C - Temperate (Mesothermal) Climates |
| Spain | 4 | 3 | Class C - Temperate (Mesothermal) Climates |
| Sweden | 4 | 3 | Class D - Continental (Microthermal) Climates |
| United Kingdom | 4 | 3 | Class C - Temperate (Mesothermal) Climates |
Most in Excess Death Class 1 & 2 (e.g. Russia, Hungary, Ukraine)
48% in Stringency Class 3
85% (23/27 countries) in Temperate (Mesothermal) Climates
|
|
|
Cluster 2 countries profile – other variables
Cluster 3: 20 Countries
| location | excess_death_class | stringency_class | Climateclass |
|---|---|---|---|
| Kyrgyzstan | 1 | 1 | Class C - Temperate (Mesothermal) Climates |
| Ukraine | 1 | 1 | Class D - Continental (Microthermal) Climates |
| Azerbaijan | 2 | 3 | Class B - Dry (Arid and Semiarid) Climates |
| Brazil | 2 | 3 | Class A - Tropical Climates |
| Colombia | 2 | 3 | Class A - Tropical Climates |
| Costa Rica | 2 | 1 | Class A - Tropical Climates |
| Ecuador | 2 | 1 | Class A - Tropical Climates |
| Guatemala | 2 | 1 | Class A - Tropical Climates |
| Iran | 2 | 4 | Class B - Dry (Arid and Semiarid) Climates |
| Mexico | 2 | 3 | Class B - Dry (Arid and Semiarid) Climates |
| Oman | 2 | 3 | Class B - Dry (Arid and Semiarid) Climates |
| Paraguay | 2 | 1 | Class C - Temperate (Mesothermal) Climates |
| Peru | 2 | 1 | Class A - Tropical Climates |
| Qatar | 2 | 2 | Class B - Dry (Arid and Semiarid) Climates |
| South Africa | 2 | 1 | Class B - Dry (Arid and Semiarid) Climates |
| Uzbekistan | 2 | 1 | Class B - Dry (Arid and Semiarid) Climates |
| Mongolia | 3 | 3 | Class D - Continental (Microthermal) Climates |
| Thailand | 3 | 1 | Class A - Tropical Climates |
| Bolivia | 4 | 1 | Class A - Tropical Climates |
| Egypt | 4 | 1 | Class B - Dry (Arid and Semiarid) Climates |
| Kazakhstan | 4 | 1 | Class D - Continental (Microthermal) Climates |
|
|
|
Cluster 3 countries profile – other variables
All 3 Clusters Profiles Together
| Cluster 1 | Cluster 2 | Cluster 3 | |
|---|---|---|---|
| Number of Countries | 28 | 21 | 21 |
| Personal Freedom | 17.8 | 21.6 | 14.7 |
| Social Network | 13.25 | 15.1 | 14.9 |
| Assembly Freedom | 15.85 | 18.2 | 12.1 |
| Health Preventions | 13.05 | 13.6 | 12.7 |
| Social & Civic Participartion | 6 | 9.8 | 5.7 |
| Government Effect | 13.5 | 18.2 | 9.4 |
| Personal & Family Relationships | 16.05 | 16.2 | 15.4 |
| Population Density | 103.75 | 127.66 | 49.83 |
| Median Age | 42.15 | 42.3 | 29.3 |
| Aged 65 Older | 16.67 | 18.57 | 6.38 |
| GDP per capita | 25723.07 | 42658.58 | 12294.88 |
| Life Expectancy | 78.2 | 82.29 | 74.3 |
| Dominate Climate Class | Temperate (21) | Temperate (16) | Tropical (8) & Dry (8) |
| Excess Death Class | Class 1 (23) | Class 3 (12) & Class 4 (6) | Class 2 (14) |
| Stringency Class | Class 2 (14) | Class 1 (7) & Class 3 (6) | Class 1 (13) |
Multinomial Regression (DV – membership)
Model Summary
library(rsample)
data2$cluster <- relevel(as.factor(data2$cluster), ref = 2)
#data3 <- cbind(data2[c(2,3,17,18)], data2_mat[-1])
data_split <- initial_split(data2, prop = .75)
data_train <- training(data_split)[-1]
data_test <- testing(data_split)[-1]library(nnet)
# Run a "only intercept" model
OIM <- multinom(cluster ~ 1, data = data_train)## # weights: 6 (2 variable)
## initial value 57.127839
## final value 55.011082
## convergedsummary(OIM)## Call:
## multinom(formula = cluster ~ 1, data = data_train)
##
## Coefficients:
## (Intercept)
## 1 0.6931382
## 3 0.2876844
##
## Std. Errors:
## (Intercept)
## 1 0.3535533
## 3 0.3818805
##
## Residual Deviance: 110.0222
## AIC: 114.0222model <- multinom(cluster ~ ., data = data_train)## # weights: 75 (48 variable)
## initial value 57.127839
## iter 10 value 39.785450
## iter 20 value 25.813878
## iter 30 value 14.242741
## iter 40 value 4.332693
## iter 50 value 1.149111
## iter 60 value 0.694271
## iter 70 value 0.199253
## iter 80 value 0.001933
## final value 0.000070
## convergedsummary(model)## Call:
## multinom(formula = cluster ~ ., data = data_train)
##
## Coefficients:
## (Intercept) stringency_class2 stringency_class3 stringency_class4
## 1 0.2011209 44.69120 1.29686 -12.71315
## 3 2.8338406 3.27084 -18.84317 -2.07353
## excess_death_class2 excess_death_class3 excess_death_class4 persfreedomagency
## 1 -22.72021 -52.434381 -38.65150 -3.808105
## 3 23.26141 4.253669 -20.39654 -1.341068
## Socialcapsocialnetwork healthprevent Socialcapcivic PersonalFreedom
## 1 5.957351 4.032275 -7.258347 -16.39476
## 3 9.947543 -22.422292 -15.590572 -19.84797
## GovernanGovernmeffect Socialcappersonalandfamily population
## 1 -3.643599 23.14000 1.304769e-07
## 3 3.058993 28.64148 3.520898e-07
## population_density median_age aged_65_older gdp_per_capita life_expectancy
## 1 -0.00520635 9.450095 -9.989834 0.0004135370 -3.0189138
## 3 -0.04990555 14.740756 -28.531516 -0.0004721791 -0.4675843
## ClimateclassClass A - Tropical Climates
## 1 8.668774
## 3 1.738141
## ClimateclassClass B - Dry (Arid and Semiarid) Climates
## 1 1.523988
## 3 -12.170969
## ClimateclassClass C - Temperate (Mesothermal) Climates
## 1 -10.30552
## 3 -18.36052
## ClimateclassClass D - Continental (Microthermal) Climates
## 1 0.313875
## 3 31.627187
##
## Std. Errors:
## (Intercept) stringency_class2 stringency_class3 stringency_class4
## 1 2.379864e-08 9.499079e-13 1.506251e-10 9.049431e-16
## 3 2.880106e-12 1.870112e-17 2.066874e-12 2.251054e-23
## excess_death_class2 excess_death_class3 excess_death_class4 persfreedomagency
## 1 1.662904e-13 3.555299e-12 7.128628e-11 4.969946e-07
## 3 1.662904e-13 1.757223e-12 2.066874e-12 5.822978e-11
## Socialcapsocialnetwork healthprevent Socialcapcivic PersonalFreedom
## 1 3.178201e-07 3.094111e-07 1.986372e-07 4.376837e-07
## 3 4.845397e-11 4.076768e-11 2.487593e-11 4.421269e-11
## GovernanGovernmeffect Socialcappersonalandfamily population
## 1 4.157653e-07 3.709867e-07 1.141654e-05
## 3 3.891435e-11 4.537851e-11 1.265396e-05
## population_density median_age aged_65_older gdp_per_capita life_expectancy
## 1 4.821129e-06 9.638916e-07 3.645553e-07 1.927747e-03 1.940643e-06
## 3 2.936307e-10 1.052720e-10 2.875184e-11 5.076802e-08 2.340195e-10
## ClimateclassClass A - Tropical Climates
## 1 1.922734e-12
## 3 1.922734e-12
## ClimateclassClass B - Dry (Arid and Semiarid) Climates
## 1 3.872303e-12
## 3 2.066874e-12
## ClimateclassClass C - Temperate (Mesothermal) Climates
## 1 2.379392e-08
## 3 2.807775e-19
## ClimateclassClass D - Continental (Microthermal) Climates
## 1 1.068146e-12
## 3 1.106826e-12
##
## Residual Deviance: 0.0001400342
## AIC: 92.00014Interpretation of the Model Fit information
## Model
## 1 1
## 2 stringency_class + excess_death_class + persfreedomagency + Socialcapsocialnetwork + healthprevent + Socialcapcivic + PersonalFreedom + GovernanGovernmeffect + Socialcappersonalandfamily + population + population_density + median_age + aged_65_older + gdp_per_capita + life_expectancy + Climateclass
## Resid. df Resid. Dev Test Df LR stat. Pr(Chi)
## 1 102 1.100222e+02 NA NA NA
## 2 58 1.400342e-04 1 vs 2 44 110.022 1.418297e-07Get p-values
# Calculate z-score for the model (wald Z)
zvalues <- summary(model)$coefficients / summary(model)$standard.errors
# Calculate p-values
#pnorm(abs(zvalues), lower.tail = FALSE)*2
# 2-tailed z test
p <- (1 - pnorm(abs(zvalues), 0, 1)) * 2
p## (Intercept) stringency_class2 stringency_class3 stringency_class4
## 1 0 0 0 0
## 3 0 0 0 0
## excess_death_class2 excess_death_class3 excess_death_class4 persfreedomagency
## 1 0 0 0 0
## 3 0 0 0 0
## Socialcapsocialnetwork healthprevent Socialcapcivic PersonalFreedom
## 1 0 0 0 0
## 3 0 0 0 0
## GovernanGovernmeffect Socialcappersonalandfamily population
## 1 0 0 0.9908814
## 3 0 0 0.9778021
## population_density median_age aged_65_older gdp_per_capita life_expectancy
## 1 0 0 0 0.8301429 0
## 3 0 0 0 0.0000000 0
## ClimateclassClass A - Tropical Climates
## 1 0
## 3 0
## ClimateclassClass B - Dry (Arid and Semiarid) Climates
## 1 0
## 3 0
## ClimateclassClass C - Temperate (Mesothermal) Climates
## 1 0
## 3 0
## ClimateclassClass D - Continental (Microthermal) Climates
## 1 0
## 3 0Training test accuracy %
# predicting values for train dataset
data_train$cluster_predicted <- predict(model, newdata = data_train, "class")
# building classification table
tab_train <- table(data_train$cluster, data_train$cluster_predicted)
# Calculating accuracy - sum of diagonal elements divided by total obs
round((sum(diag(tab_train))/sum(tab_train))*100,2)## [1] 100Test set accuracy %
data_test$cluster_predicted <- predict(model, newdata = data_test, "class")
tab_test <- table(data_test$cluster, data_test$cluster_predicted)
round((sum(diag(tab_test))/sum(tab_test))*100,2)## [1] 94.44##
## Pearson's Chi-squared test
##
## data: data_test$cluster and data_test$cluster_predicted
## X-squared = 30.8, df = 4, p-value = 3.363e-06Exponentiate model coefficients
## extract the coefficients from the model and exponentiate
exp(coef(model))## (Intercept) stringency_class2 stringency_class3 stringency_class4
## 1 1.222773 2.565324e+19 3.657793e+00 3.011271e-06
## 3 17.010666 2.633346e+01 6.554113e-09 1.257412e-01
## excess_death_class2 excess_death_class3 excess_death_class4 persfreedomagency
## 1 1.357494e-10 1.690588e-23 1.636309e-17 0.0221902
## 3 1.265622e+10 7.036307e+01 1.386418e-09 0.2615662
## Socialcapsocialnetwork healthprevent Socialcapcivic PersonalFreedom
## 1 386.5846 5.638907e+01 7.042716e-04 7.583107e-08
## 3 20900.7977 1.828615e-10 1.694730e-07 2.399579e-09
## GovernanGovernmeffect Socialcappersonalandfamily population
## 1 0.02615804 1.120923e+10 1
## 3 21.30608860 2.746848e+12 1
## population_density median_age aged_65_older gdp_per_capita life_expectancy
## 1 0.9948072 12709.38 4.586382e-05 1.0004136 0.04885425
## 3 0.9513193 2522486.27 4.063685e-13 0.9995279 0.62651392
## ClimateclassClass A - Tropical Climates
## 1 5818.362742
## 3 5.686763
## ClimateclassClass B - Dry (Arid and Semiarid) Climates
## 1 4.590497e+00
## 3 5.178636e-06
## ClimateclassClass C - Temperate (Mesothermal) Climates
## 1 3.344807e-05
## 3 1.062009e-08
## ClimateclassClass D - Continental (Microthermal) Climates
## 1 1.368719e+00
## 3 5.438921e+13