qualitycontrolThe goal of qualitycontrol is to set a data quality
control framework
You can install the qualitycontrol from GitHub with:
The als_data dataset will be used to guide you through
the package functionality. This data is not real, but based on data
retrieved from Amyotrophic Lateral Sclerosis patients.
library(qualitycontrol)
als_data
#> subjid p1 p2 p3 p4 p5 p6 p7 p8 p9 x1r x2r x3r age_at_baseline age_at_onset
#> 1 1 4 1 1 3 4 3 4 3 4 2 2 1 51 46
#> 2 2 4 4 4 1 1 3 3 1 4 1 2 4 82 77
#> 3 3 2 3 1 4 3 1 3 1 1 4 3 1 85 80
#> 4 4 3 2 1 1 4 1 3 2 4 4 3 3 77 72
#> 5 5 3 2 1 3 3 4 4 3 4 1 4 2 85 80
#> 6 6 2 2 1 4 1 4 4 3 1 3 5 2 73 68
#> 7 7 1 4 2 4 3 3 2 3 4 1 2 2 65 60
#> 8 8 2 2 4 4 3 2 1 2 3 3 1 1 50 62
#> 9 9 3 1 1 4 4 2 4 1 1 2 2 4 65 46
#> 10 10 3 4 1 4 3 2 3 2 1 4 3 1 81 76
#> 11 11 1 3 1 3 3 4 1 NA 3 3 2 4 51 46
#> 12 12 1 4 3 2 3 2 2 NA 1 3 2 3 50 45
#> 13 13 1 1 4 1 1 3 4 NA 2 2 3 1 82 77
#> 14 14 3 2 2 4 3 3 3 3 2 3 4 1 76 71
#> 15 15 3 4 2 2 2 3 1 3 4 4 1 4 87 376
#> 16 16 3 3 2 4 3 3 1 1 2 2 4 1 50 45
#> 17 17 3 2 3 1 4 1 3 2 1 4 4 2 85 80
#> 18 18 4 1 3 1 3 1 3 2 2 4 3 4 57 52
#> 19 19 1 3 3 2 2 2 3 2 3 2 3 2 74 69
#> 20 20 2 2 4 2 3 4 2 4 1 4 1 3 59 54
#> 21 21 2 3 3 2 3 2 4 4 1 1 3 3 79 74
#> 22 22 4 3 1 1 3 4 2 1 4 1 2 3 53 48
#> 23 23 3 3 4 3 4 1 3 4 3 2 2 2 45 40
#> 24 24 4 1 1 2 4 2 4 4 4 4 2 1 72 67
#> 25 25 4 3 1 3 3 4 3 2 3 3 4 2 77 72
#> 26 26 2 1 1 2 4 2 4 1 2 3 2 4 65 60
#> 27 27 1 1 1 1 1 1 3 3 2 2 1 1 54 49
#> 28 28 3 1 1 3 1 4 1 2 2 2 3 4 50 -23
#> 29 29 2 3 1 3 1 4 4 1 3 2 4 1 85 80
#> 30 30 3 1 2 1 3 1 2 4 1 1 2 4 85 80
#> 31 30 3 3 1 4 2 2 1 4 3 3 1 3 53 48
#> onset baseline_date death_date
#> 1 bulbar 2003-03-26 2010-10-18
#> 2 bulba 2003-07-03 2019-06-24
#> 3 spinal 2007-01-27 9999-12-30
#> 4 bulbar 2010-11-27 2018-01-04
#> 5 bulbar 2006-10-25 2017-10-13
#> 6 spinal 2007-04-30 2010-05-08
#> 7 spinal 2002-11-15 2019-04-06
#> 8 spinal 2002-12-13 2018-05-04
#> 9 spinal 2005-06-02 2013-08-11
#> 10 bulbar 2004-06-02 2016-05-20
#> 11 bulbar 2007-03-09 2016-09-26
#> 12 bulbar 2005-01-11 2010-06-20
#> 13 bulbar 2010-12-22 2019-07-05
#> 14 bulbar 2008-10-14 2013-08-14
#> 15 spinal 2005-09-15 2010-07-20
#> 16 spinal 2007-07-05 2010-08-28
#> 17 respiratory 2002-08-19 2011-10-17
#> 18 spinal 2002-06-30 2020-12-17
#> 19 respiratory 2010-07-18 2016-05-15
#> 20 spinal 2004-08-15 2015-03-15
#> 21 bulbar 2006-04-07 2013-03-16
#> 22 bulbar 2002-06-01 2016-06-21
#> 23 bulbar 2007-08-12 2017-04-01
#> 24 bulbar 2006-08-12 2002-12-02
#> 25 respiratory 2006-08-11 2016-03-03
#> 26 spinal 2005-01-04 2011-10-05
#> 27 respiratory 2009-08-25 2015-03-11
#> 28 bulbar 2002-05-11 2017-11-09
#> 29 bulbar 2004-07-27 2014-03-27
#> 30 bulbar 2005-11-11 2015-05-30
#> 31 bulbar 2008-02-27 2014-07-05The als_data_qc_mapping is an R list which
contains 3 tables specifying all the tests used for quality control.
als_data_qc_mapping$missing
#> # A tibble: 13 × 3
#> qc_type variable type
#> <chr> <chr> <chr>
#> 1 duplicated subjid text
#> 2 missing p1 numeric
#> 3 missing p2 numeric
#> 4 missing p3 numeric
#> 5 missing p4 numeric
#> 6 missing p5 numeric
#> 7 missing p6 numeric
#> 8 missing p7 numeric
#> 9 missing p8 numeric
#> 10 missing p9 numeric
#> 11 missing x1r numeric
#> 12 missing x2r numeric
#> 13 missing x3r numericals_data_qc_mapping$inconsistencies
#> # A tibble: 2 × 6
#> qc_type variable1 type1 relation variable2 type2
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 inconsistent_values age_at_baseline numeric greater_than age_at_onset numeric
#> 2 inconsistent_values baseline_date date lower_than death_date dateals_data_qc_mapping$range
#> # A tibble: 16 × 6
#> qc_type variable type lower_value upper_value categories
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 range p1 numeric 1 4 <NA>
#> 2 range p2 numeric 1 4 <NA>
#> 3 range p3 numeric 1 4 <NA>
#> 4 range p4 numeric 1 4 <NA>
#> 5 range p5 numeric 1 4 <NA>
#> 6 range p6 numeric 1 4 <NA>
#> 7 range p7 numeric 1 4 <NA>
#> 8 range p8 numeric 1 4 <NA>
#> 9 range p9 numeric 1 4 <NA>
#> 10 range x1r numeric 1 4 <NA>
#> 11 range x2r numeric 1 4 <NA>
#> 12 range x3r numeric 1 4 <NA>
#> 13 range age_at_baseline numeric 20 100 <NA>
#> 14 range age_at_onset numeric 20 100 <NA>
#> 15 range death_date date 2000-01-01 2022-01-01 <NA>
#> 16 range onset categorical <NA> <NA> bulbar, respirat…qc_data functionqc_data takes as arguments the data to be quality
controlled and the QC mapping containing the tests to be applied.
qc_data(als_data, als_data_qc_mapping)
#> # A tibble: 13 × 19
#> subjid p1 p2 p3 p4 p5 p6 p7 p8 p9 x1r x2r
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 30 3 1 2 1 3 1 2 4 1 1 2
#> 2 30 3 3 1 4 2 2 1 4 3 3 1
#> 3 11 1 3 1 3 3 4 1 <NA> 3 3 2
#> 4 12 1 4 3 2 3 2 2 <NA> 1 3 2
#> 5 13 1 1 4 1 1 3 4 <NA> 2 2 3
#> 6 6 2 2 1 4 1 4 4 3 1 3 5
#> 7 15 3 4 2 2 2 3 1 3 4 4 1
#> 8 28 3 1 1 3 1 4 1 2 2 2 3
#> 9 3 2 3 1 4 3 1 3 1 1 4 3
#> 10 2 4 4 4 1 1 3 3 1 4 1 2
#> 11 8 2 2 4 4 3 2 1 2 3 3 1
#> 12 15 3 4 2 2 2 3 1 3 4 4 1
#> 13 24 4 1 1 2 4 2 4 4 4 4 2
#> # ℹ 7 more variables: x3r <chr>, age_at_baseline <chr>, age_at_onset <chr>,
#> # onset <chr>, baseline_date <chr>, death_date <chr>, finding <chr>This will return a table with all the findings. If you want to save
it, you can specify the path to be saved in
output_file.