Data report overview

The dataset examined has the following dimensions:

Feature	Result
Number of observations	257
Number of variables	149

Only variables that were deemed potentially problematic are included in this summary.

Checks performed

The following variable checks were performed, depending on the data type of each variable:

	character	factor	labelled	numeric	integer	Date
Identify miscoded missing values	×	×	×	×	×	×
Identify prefixed and suffixed whitespace	×	×	×
Identify levels with < 6 obs.	×	×	×
Identify case issues	×	×	×
Identify misclassified numeric or integer variables	×	×	×
Identify outliers				×	×	×

Please note that all numerical values in the following have been rounded to 2 decimals.

Summary table

	Variable class	# unique values	Any problems?
ID	character	257	×
Rum22	integer	7	×
Sav2	integer	8	×
Sav3	integer	6	×
Sav6	integer	8	×
Sav9	integer	7	×
Sav14	integer	8	×
Sav15	integer	6	×
Sav16	integer	8	×
Sav18	integer	8	×
Sav19	integer	7	×
Sav21	integer	6	×
Sav22	integer	8	×
LS3	integer	8	×
LS4	integer	8	×
Dependable	integer	6	×
NewExperiences	integer	7	×
Sympathetic	integer	6	×
Disorganized	integer	7	×
Calm	integer	7	×
Conventional	integer	5	×
Health2	integer	5	×
Health4	integer	4	×
Health5	integer	5	×
Health6	integer	5	×
Health7	integer	5	×
Health8	integer	5	×
Health10	integer	5	×
Health11	integer	4	×
Health15	integer	5	×
Health16	integer	5	×
Health17	integer	5	×
Health18	integer	5	×
Health19	integer	5	×
Health20	integer	5	×
Health23	integer	5	×
Health24	integer	5	×
Health25	integer	5	×
Health26	integer	5	×
Health27	integer	4	×
Health29	integer	5	×
Health31	integer	4	×
Health32	integer	5	×
Dep2	integer	4	×
Dep3	integer	4	×
Dep6	integer	4	×
Dep8	integer	4	×
Dep13	integer	4	×
Dep15	integer	4	×
RRS	numeric	38	×
RRS_D	numeric	26	×
RRS_R	numeric	15	×
Sav2R	numeric	8	×
Sav6R	numeric	8	×
Sav14R	numeric	8	×
Sav16R	numeric	8	×
Sav18R	numeric	8	×
Sav22R	numeric	8	×
SBI	numeric	30	×
SavPos	numeric	33	×
SavNeg	integer	29	×
Anticipating	numeric	19	×
Reminiscing	numeric	20	×
SWLS	numeric	21	×
DisR	numeric	7	×
ConvR	numeric	5	×
Agree	numeric	10	×
Consc	numeric	11	×
EmoSt	numeric	10	×
Openness	numeric	9	×
Dep8R	numeric	4	×
CESD	numeric	17	×

Variable list

ID

The variable is a key (distinct values for each observation).

Rum22

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	7
Median	1
1st and 3rd quartiles	1; 2
Min. and max.	0; 6

Note that the following possible outlier values were detected: "0".

Sav2

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	8
Median	2
1st and 3rd quartiles	2; 3
Min. and max.	0; 7

Note that the following possible outlier values were detected: "0", "1".

Sav3

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	6
Median	6
1st and 3rd quartiles	6; 7
Min. and max.	2; 7

Note that the following possible outlier values were detected: "2", "3", "4".

Sav6

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	8
Median	2
1st and 3rd quartiles	1; 3
Min. and max.	0; 7

Note that the following possible outlier values were detected: "7".

Sav9

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	7
Median	6
1st and 3rd quartiles	5; 6
Min. and max.	1; 7

Note that the following possible outlier values were detected: "7".

Sav14

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	8
Median	2
1st and 3rd quartiles	2; 3
Min. and max.	0; 7

Note that the following possible outlier values were detected: "0", "1".

Sav15

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	6
Median	6
1st and 3rd quartiles	5; 6
Min. and max.	2; 7

Note that the following possible outlier values were detected: "7".

Sav16

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	8
Median	2
1st and 3rd quartiles	2; 3
Min. and max.	0; 7

Note that the following possible outlier values were detected: "0", "1".

Sav18

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	8
Median	2
1st and 3rd quartiles	1; 3
Min. and max.	0; 7

Note that the following possible outlier values were detected: "7".

Sav19

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	7
Median	6
1st and 3rd quartiles	4; 6
Min. and max.	1; 7

Note that the following possible outlier values were detected: "7".

Sav21

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	6
Median	6
1st and 3rd quartiles	4; 6
Min. and max.	2; 7

Note that the following possible outlier values were detected: "7".

Sav22

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	8
Median	2
1st and 3rd quartiles	2; 3
Min. and max.	0; 7

Note that the following possible outlier values were detected: "0", "1".

LS3

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	8
Median	6
1st and 3rd quartiles	4; 6
Min. and max.	0; 7

Note that the following possible outlier values were detected: "7".

LS4

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	8
Median	6
1st and 3rd quartiles	4; 6
Min. and max.	0; 7

Note that the following possible outlier values were detected: "7".

Dependable

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	6
Median	6
1st and 3rd quartiles	5; 6
Min. and max.	2; 7

Note that the following possible outlier values were detected: "7".

NewExperiences

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	7
Median	6
1st and 3rd quartiles	5; 6
Min. and max.	0; 7

Note that the following possible outlier values were detected: "7".

Sympathetic

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	6
Median	6
1st and 3rd quartiles	5; 6
Min. and max.	2; 7

Note that the following possible outlier values were detected: "7".

Disorganized

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	7
Median	5
1st and 3rd quartiles	4; 6
Min. and max.	0; 7

Note that the following possible outlier values were detected: "0".

Calm

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	7
Median	6
1st and 3rd quartiles	4; 6
Min. and max.	1; 7

Note that the following possible outlier values were detected: "7".

Conventional

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	5
Mode	“3”

Note that the following levels have at most five observations: "0", "1".

Health2

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	5
Mode	“1”

Note that the following levels have at most five observations: "4".

Health4

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	4
Mode	“0”

Note that the following levels have at most five observations: "3".

Health5

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	5
Mode	“0”

Note that the following levels have at most five observations: "4".

Health6

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	5
Mode	“0”

Note that the following levels have at most five observations: "4".

Health7

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	5
Mode	“0”

Note that the following levels have at most five observations: "4".

Health8

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	5
Mode	“1”

Note that the following levels have at most five observations: "4".

Health10

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	5
Mode	“0”

Note that the following levels have at most five observations: "4".

Health11

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	4
Mode	“0”

Note that the following levels have at most five observations: "3".

Health15

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	5
Mode	“0”

Note that the following levels have at most five observations: "4".

Health16

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	5
Mode	“0”

Note that the following levels have at most five observations: "4".

Health17

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	5
Mode	“1”

Note that the following levels have at most five observations: "4".

Health18

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	5
Mode	“0”

Note that the following levels have at most five observations: "4".

Health19

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	5
Mode	“0”

Note that the following levels have at most five observations: "4".

Health20

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	5
Mode	“0”

Note that the following levels have at most five observations: "4".

Health23

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	5
Mode	“1”

Note that the following levels have at most five observations: "4".

Health24

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	5
Mode	“0”

Note that the following levels have at most five observations: "3", "4".

Health25

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	5
Mode	“1”

Note that the following levels have at most five observations: "4".

Health26

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	5
Mode	“0”

Note that the following levels have at most five observations: "4".

Health27

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	4
Mode	“0”

Note that the following levels have at most five observations: "3".

Health29

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	5
Mode	“0”

Note that the following levels have at most five observations: "4".

Health31

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	4
Mode	“0”

Note that the following levels have at most five observations: "3".

Health32

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	5
Mode	“1”

Note that the following levels have at most five observations: "4".

Dep2

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	4
Mode	“0”

Note that the following levels have at most five observations: "3".

Dep3

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	4
Mode	“0”

Note that the following levels have at most five observations: "3".

Dep6

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	4
Mode	“0”

Note that the following levels have at most five observations: "3".

Dep8

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	4
Mode	“0”

Note that the following levels have at most five observations: "3".

Dep13

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	4
Mode	“0”

Note that the following levels have at most five observations: "3".

Dep15

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	4
Mode	“0”

Note that the following levels have at most five observations: "3".

RRS

Feature	Result
Variable type	numeric
Number of missing obs.	0 (0 %)
Number of unique values	38
Median	37
1st and 3rd quartiles	32; 43
Min. and max.	17; 60

Note that the following possible outlier values were detected: "60".

RRS_D

Feature	Result
Variable type	numeric
Number of missing obs.	0 (0 %)
Number of unique values	26
Median	21
1st and 3rd quartiles	17; 24
Min. and max.	10; 37

Note that the following possible outlier values were detected: "36", "37".

RRS_R

Feature	Result
Variable type	numeric
Number of missing obs.	0 (0 %)
Number of unique values	15
Median	8
1st and 3rd quartiles	6; 10
Min. and max.	1; 17

Note that the following possible outlier values were detected: "17".

Sav2R

Feature	Result
Variable type	numeric
Number of missing obs.	0 (0 %)
Number of unique values	8
Median	6
1st and 3rd quartiles	5; 6
Min. and max.	1; 8

Note that the following possible outlier values were detected: "7", "8".

Sav6R

Feature	Result
Variable type	numeric
Number of missing obs.	0 (0 %)
Number of unique values	8
Median	6
1st and 3rd quartiles	5; 7
Min. and max.	1; 8

Note that the following possible outlier values were detected: "1".

Sav14R

Feature	Result
Variable type	numeric
Number of missing obs.	0 (0 %)
Number of unique values	8
Median	6
1st and 3rd quartiles	5; 6
Min. and max.	1; 8

Note that the following possible outlier values were detected: "7", "8".

Sav16R

Feature	Result
Variable type	numeric
Number of missing obs.	0 (0 %)
Number of unique values	8
Median	6
1st and 3rd quartiles	5; 6
Min. and max.	1; 8

Note that the following possible outlier values were detected: "7", "8".

Sav18R

Feature	Result
Variable type	numeric
Number of missing obs.	0 (0 %)
Number of unique values	8
Median	6
1st and 3rd quartiles	5; 7
Min. and max.	1; 8

Note that the following possible outlier values were detected: "1".

Sav22R

Feature	Result
Variable type	numeric
Number of missing obs.	0 (0 %)
Number of unique values	8
Median	6
1st and 3rd quartiles	5; 6
Min. and max.	1; 8

Note that the following possible outlier values were detected: "7", "8".

SBI

Feature	Result
Variable type	numeric
Number of missing obs.	0 (0 %)
Number of unique values	30
Median	131
1st and 3rd quartiles	128; 137
Min. and max.	114; 151

Note that the following possible outlier values were detected: "114", "118".

SavPos

Feature	Result
Variable type	numeric
Number of missing obs.	0 (0 %)
Number of unique values	33
Median	66
1st and 3rd quartiles	61; 70
Min. and max.	37; 83

Note that the following possible outlier values were detected: "37", "78", "80", "81", "83".

SavNeg

Feature	Result
Variable type	integer
Number of missing obs.	0 (0 %)
Number of unique values	29
Median	67
1st and 3rd quartiles	64; 71
Min. and max.	49; 78

Note that the following possible outlier values were detected: "49", "50", "51", "53".

Anticipating

Feature	Result
Variable type	numeric
Number of missing obs.	0 (0 %)
Number of unique values	19
Median	44
1st and 3rd quartiles	41; 46
Min. and max.	35; 54

Note that the following possible outlier values were detected: "54".

Reminiscing

Feature	Result
Variable type	numeric
Number of missing obs.	0 (0 %)
Number of unique values	20
Median	45
1st and 3rd quartiles	43; 47
Min. and max.	32; 54

Note that the following possible outlier values were detected: "32", "36", "54".

SWLS

Feature	Result
Variable type	numeric
Number of missing obs.	0 (0 %)
Number of unique values	21
Median	24
1st and 3rd quartiles	22; 27
Min. and max.	13; 33

Note that the following possible outlier values were detected: "13", "14".

DisR

Feature	Result
Variable type	numeric
Number of missing obs.	0 (0 %)
Number of unique values	7
Median	3
1st and 3rd quartiles	2; 4
Min. and max.	1; 8

The following suspected missing value codes enter as regular values: "8".
Note that the following possible outlier values were detected: "8".

ConvR

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	numeric
Number of missing obs.	0 (0 %)
Number of unique values	5
Mode	“5”

The following suspected missing value codes enter as regular values: "8".
Note that the following levels have at most five observations: "7", "8".

Agree

Feature	Result
Variable type	numeric
Number of missing obs.	0 (0 %)
Number of unique values	10
Median	4.5
1st and 3rd quartiles	4; 5
Min. and max.	2; 6.5

Note that the following possible outlier values were detected: "2".

Consc

Feature	Result
Variable type	numeric
Number of missing obs.	0 (0 %)
Number of unique values	11
Median	4
1st and 3rd quartiles	4; 5
Min. and max.	1.5; 6.5

Note that the following possible outlier values were detected: "1.5", "2", "2.5", "3", "3.5".

EmoSt

Feature	Result
Variable type	numeric
Number of missing obs.	0 (0 %)
Number of unique values	10
Median	4.5
1st and 3rd quartiles	3.5; 5
Min. and max.	2; 6.5

Note that the following possible outlier values were detected: "6.5".

Openness

Feature	Result
Variable type	numeric
Number of missing obs.	0 (0 %)
Number of unique values	9
Median	5.5
1st and 3rd quartiles	5; 6
Min. and max.	3; 7

Note that the following possible outlier values were detected: "6.5", "7".

Dep8R

Note that this variable is treated as a factor variable below, as it only takes a few unique values.

Feature	Result
Variable type	numeric
Number of missing obs.	0 (0 %)
Number of unique values	4
Mode	“3”

Note that the following levels have at most five observations: "0".

CESD

Feature	Result
Variable type	numeric
Number of missing obs.	0 (0 %)
Number of unique values	17
Median	15
1st and 3rd quartiles	13; 18
Min. and max.	8; 25

Note that the following possible outlier values were detected: "8", "9".

Report generation information:

Created by Sara Locatelli.
Report creation time: Mon Apr 16 2018 10:12:39
dataMaid v1.1.0 [Pkg: 2018-02-06 from CRAN (R 3.4.3)]
R version 3.4.4 (2018-03-15).
Platform: x86_64-apple-darwin15.6.0 (64-bit)(macOS High Sierra 10.13.3).
Function call: makeDataReport(data = Facebook, output = "html", render = FALSE, onlyProblematic = TRUE, file = "report_Facebook_sum.Rmd", replace = TRUE)

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Autogenerated data summary from dataMaid

2018-04-16 10:12:38