Workshop on Mixed Effects Model

Cài đặt online các packages: table1, compareGroups, sjPlot, và sjmisc

#install.packages(c('table1', 'compareGroups', 'sjPlot', 'sjmisc'), dependencies = T)

Task 1: Đọc dữ liệu

Mở RStudio và chọn RMarkdown.
Đọc dữ liệu PISA Data Vietnam 2015.csv vào R và gọi đối tượng là pisa.
Tìm hiểu dữ liệu có bao nhiêu ca (dòng) và bao nhiêu cột: dim(pisa).

pisa= read.csv("C:/Users/ADMIN/OneDrive/Statistical courses/Ton Duc Thang_Jan2020/TDTU Datasets for 2020 Workshop/PISA Data Vietnam 2015.csv")
dim (pisa)

## [1] 5826   18

Liệt kê 6 dòng đầu tiên: head(pisa)

head (pisa)

##     School SchoolSize ClassSize STratio SchoolType  Area Region   Age
## 1 70400001        883        18  22.075          3 URBAN  SOUTH 15.58
## 2 70400001        883        18  22.075          3 URBAN  SOUTH 15.92
## 3 70400001        883        18  22.075          3 URBAN  SOUTH 15.42
## 4 70400001        883        18  22.075          3 URBAN  SOUTH 15.58
## 5 70400001        883        18  22.075          3 URBAN  SOUTH 15.92
## 6 70400001        883        18  22.075          3 URBAN  SOUTH 16.25
##   Gender PARED HISCED  WEALTH INSTSCIE JOYSCIE  ICTRES    Math    Read
## 1   Boys     9      2 -2.0697   0.9798  2.1635 -1.5244 439.923 412.290
## 2   Boys    12      4 -1.7903   1.7359  2.1635 -1.9305 406.251 409.598
## 3  Girls     9      2 -2.1942  -0.2063 -0.1808 -1.6093 414.369 384.307
## 4  Girls     5      1 -2.0301  -0.3115 -0.4318 -1.6250 468.801 459.104
## 5  Girls     9      2 -1.0522   0.7648  1.3031 -0.5305 355.432 402.435
## 6  Girls     5      1 -3.0570   0.3708  0.5094 -2.5873 458.955 483.885
##   Science
## 1 475.612
## 2 450.320
## 3 405.787
## 4 462.968
## 5 453.736
## 6 529.866

Tóm tắt dữ liệu: summary(pisa)

summary (pisa)

##      School           SchoolSize     ClassSize        STratio      
##  Min.   :70400001   Min.   : 113   Min.   :13.00   Min.   : 4.314  
##  1st Qu.:70400052   1st Qu.: 650   1st Qu.:38.00   1st Qu.:14.024  
##  Median :70400096   Median :1090   Median :38.00   Median :16.627  
##  Mean   :70400097   Mean   :1082   Mean   :40.57   Mean   :16.497  
##  3rd Qu.:70400143   3rd Qu.:1419   3rd Qu.:43.00   3rd Qu.:18.983  
##  Max.   :70400188   Max.   :4016   Max.   :53.00   Max.   :38.651  
##                                    NA's   :34                      
##    SchoolType        Area          Region          Age          Gender    
##  Min.   :1.000   REMOTE: 410   CENTRAL:2006   Min.   :15.33   Boys :2786  
##  1st Qu.:3.000   RURAL :2368   NORTH  :1958   1st Qu.:15.50   Girls:3040  
##  Median :3.000   URBAN :3048   SOUTH  :1862   Median :15.75               
##  Mean   :2.849                                Mean   :15.78               
##  3rd Qu.:3.000                                3rd Qu.:16.00               
##  Max.   :3.000                                Max.   :16.25               
##  NA's   :35                                                               
##      PARED            HISCED         WEALTH          INSTSCIE      
##  Min.   : 3.000   Min.   :0.00   Min.   :-7.635   Min.   :-1.9301  
##  1st Qu.: 9.000   1st Qu.:2.00   1st Qu.:-2.829   1st Qu.: 0.0125  
##  Median : 9.000   Median :2.00   Median :-2.163   Median : 0.3708  
##  Mean   : 9.374   Mean   :2.58   Mean   :-2.219   Mean   : 0.4835  
##  3rd Qu.:12.000   3rd Qu.:4.00   3rd Qu.:-1.504   3rd Qu.: 1.0218  
##  Max.   :17.000   Max.   :6.00   Max.   : 3.211   Max.   : 1.7359  
##  NA's   :14       NA's   :14     NA's   :15       NA's   :17       
##     JOYSCIE            ICTRES            Math            Read      
##  Min.   :-2.1154   Min.   :-3.508   Min.   :201.7   Min.   :107.1  
##  1st Qu.: 0.5094   1st Qu.:-2.587   1st Qu.:440.0   1st Qu.:442.5  
##  Median : 0.5094   Median :-1.855   Median :493.4   Median :489.5  
##  Mean   : 0.6448   Mean   :-1.795   Mean   :496.1   Mean   :489.9  
##  3rd Qu.: 1.1049   3rd Qu.:-1.117   3rd Qu.:551.5   3rd Qu.:537.6  
##  Max.   : 2.1635   Max.   : 3.497   Max.   :820.1   Max.   :744.1  
##  NA's   :19        NA's   :34                                      
##     Science     
##  Min.   :292.7  
##  1st Qu.:470.9  
##  Median :523.9  
##  Mean   :524.8  
##  3rd Qu.:574.8  
##  Max.   :807.3  
##

Sắp xếp thứ tự Area bằng hàm factor

table (pisa$Area)

## 
## REMOTE  RURAL  URBAN 
##    410   2368   3048

pisa$Area = factor(pisa$Area, levels=c("URBAN", "RURAL", "REMOTE"))
table (pisa$Area)

## 
##  URBAN  RURAL REMOTE 
##   3048   2368    410

Task 2: Mã hóa (coding)

Tạo ra biến mới và gọi là Type. Nếu SchoolType == 1 thì Type= "Private"; nếu SchoolType == 3 thì Type = "Public".

pisa$Type [pisa$SchoolType == 1] = 'Private'
pisa$Type [pisa$SchoolType == 3] = 'Public'
table (pisa$Type)

## 
## Private  Public 
##     436    5355

Task 3: Phân tích mô tả pisa với package `table1`

library(table1)
table1(~ WEALTH + PARED + Math + Read + Science | Region, data=pisa)

	CENTRAL (n=2006)	NORTH (n=1958)	SOUTH (n=1862)	Overall (n=5826)
WEALTH
Mean (SD)	-2.40 (1.12)	-2.18 (1.18)	-2.06 (1.14)	-2.22 (1.16)
Median [Min, Max]	-2.33 [-7.64, 1.41]	-2.14 [-7.64, 2.63]	-2.03 [-7.64, 3.21]	-2.16 [-7.64, 3.21]
Missing	6 (0.3%)	8 (0.4%)	1 (0.1%)	15 (0.3%)
PARED
Mean (SD)	9.49 (3.44)	9.76 (3.51)	8.85 (3.54)	9.37 (3.51)
Median [Min, Max]	9.00 [3.00, 17.0]	9.00 [3.00, 17.0]	9.00 [3.00, 17.0]	9.00 [3.00, 17.0]
Missing	3 (0.1%)	9 (0.5%)	2 (0.1%)	14 (0.2%)
Math
Mean (SD)	492 (86.5)	501 (84.4)	496 (72.2)	496 (81.5)
Median [Min, Max]	488 [202, 818]	500 [251, 820]	494 [241, 719]	493 [202, 820]
Read
Mean (SD)	488 (74.3)	489 (72.4)	493 (64.4)	490 (70.6)
Median [Min, Max]	486 [233, 744]	489 [107, 718]	493 [272, 698]	489 [107, 744]
Science
Mean (SD)	524 (79.8)	523 (76.6)	528 (67.3)	525 (75.0)
Median [Min, Max]	520 [307, 807]	522 [293, 775]	528 [337, 761]	524 [293, 807]

table1(~ WEALTH + PARED + Math + Read + Science | Area, data=pisa)

	URBAN (n=3048)	RURAL (n=2368)	REMOTE (n=410)	Overall (n=5826)
WEALTH
Mean (SD)	-2.12 (1.16)	-2.22 (1.08)	-3.00 (1.25)	-2.22 (1.16)
Median [Min, Max]	-2.10 [-7.64, 3.21]	-2.16 [-7.64, 1.43]	-2.83 [-7.64, -0.0430]	-2.16 [-7.64, 3.21]
Missing	2 (0.1%)	7 (0.3%)	6 (1.5%)	15 (0.3%)
PARED
Mean (SD)	9.56 (3.48)	9.38 (3.47)	7.90 (3.69)	9.37 (3.51)
Median [Min, Max]	9.00 [3.00, 17.0]	9.00 [3.00, 17.0]	9.00 [3.00, 17.0]	9.00 [3.00, 17.0]
Missing	1 (0.0%)	5 (0.2%)	8 (2.0%)	14 (0.2%)
Math
Mean (SD)	499 (79.3)	500 (81.9)	450 (82.0)	496 (81.5)
Median [Min, Max]	497 [202, 820]	498 [273, 818]	446 [216, 696]	493 [202, 820]
Read
Mean (SD)	496 (69.6)	491 (67.6)	440 (76.0)	490 (70.6)
Median [Min, Max]	495 [107, 718]	490 [292, 744]	439 [233, 643]	489 [107, 744]
Science
Mean (SD)	527 (72.8)	529 (75.5)	482 (74.4)	525 (75.0)
Median [Min, Max]	525 [293, 799]	529 [335, 807]	475 [307, 698]	524 [293, 807]

Task 4: Phân tích mô tả pisa với package `compareGroups`

library(compareGroups)
t = compareGroups(Area ~ WEALTH + PARED + Math + Read + Science, data=pisa)
createTable(t)

## 
## --------Summary descriptives table by 'Area'---------
## 
## ________________________________________________________ 
##            URBAN        RURAL        REMOTE    p.overall 
##            N=3048       N=2368       N=410               
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯ 
## WEALTH  -2.12 (1.16) -2.22 (1.08) -3.00 (1.25)  <0.001   
## PARED   9.56 (3.48)  9.38 (3.47)  7.90 (3.69)   <0.001   
## Math     499 (79.3)   500 (81.9)   450 (82.0)   <0.001   
## Read     496 (69.6)   491 (67.6)   440 (76.0)   <0.001   
## Science  527 (72.8)   529 (75.5)   482 (74.4)   <0.001   
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯

Workshop on Mixed Effects Model - Day 1

Nguyen Van Tuan

30/12/2019

Task 1: Đọc dữ liệu

Task 2: Mã hóa (coding)

Task 3: Phân tích mô tả pisa với package `table1`

Task 4: Phân tích mô tả pisa với package `compareGroups`

Workshop on Mixed Effects Model - Day 1

Nguyen Van Tuan

30/12/2019

Task 1: Đọc dữ liệu

Task 2: Mã hóa (coding)

Task 3: Phân tích mô tả pisa với package table1

Task 4: Phân tích mô tả pisa với package compareGroups

Task 3: Phân tích mô tả pisa với package `table1`

Task 4: Phân tích mô tả pisa với package `compareGroups`