**3.4 Visual comparison of an investigated dataset with a case control dataset**

The visualisation of inconsistent data can be achieved through direct comparison of an investigating dataset with a case control dataset. Investigations that involve a comparison of an investigating dataset with a standard dataset are scenarios in which this approach can be used. This section of this chapter describes how WellGrowth app is used to enable the visual comparison of an investigated dataset with a case control dataset. It also describes the datasets investigated and how WellGrowth App was used in the investigation of the datasets.

## **3.5 Case control method**

The case–control studies approach was used in comparing two datasets where one of the datasets is the case control while the other is the investigated dataset. World Health Organisation6 (WHO) is the case control dataset and the dataset generated from Nsukka Medical Centre (NMC) is the investigated dataset. WHO data is gotten from children's empirical data which includes the length/height and weight of children at different stages of their growth for a sex matched reference. The weight and length of the children's data from WHO child growth standards for 0–12 months were used in investigating the NMC data. The average (50th percentile) score of the different children's weights and lengths in each month was used in the case control studies. This dataset is stored in WellGrowth app open source (see Section 3.22) for further analysis. The researchers collected the data (length for age and weight for age percentiles for girls and boys) directly from WHO web site (https://www.who.int/toolkits/child-growth-standards/standards/ length-height-for-age).

NMC data are the weight and length of the children's growth data from 0 to 12 months for a sex matched references which are collected from the medical center Nsukka. The average (50th percentile) score of the different children's weights and lengths in each month as curated from NMC was used in the case control studies as the investigated dataset. This dataset is stored in WellGrowth app open source (see Section 3.22) for further analysis. The data collected from the NMC were not classified. So, the researcher classified them into different files according to the sex and the growth parameter per months from 0 to 12 months. The data were collected from NMC from May to august of 2020. **Table 1** presents a record of the number

**35**

*Visual Identification of Inconsistency in Pattern DOI: http://dx.doi.org/10.5772/intechopen.95506*

child's data collected by the researchers in NMC while **Table 2** presents the 50th

**Sex Height/Length Weight** Girl 451 451 Boy 497 497

**Age/Sex Girls Boys**

 54.75 3.95 52.5 4.3 57.5 5.449 58.75 5.85 61.5 6.75 63.75 7.1 62.75 6.5 65 7.05 63.5 6.7 66 7.6 64 6.8 66.5 7.1 65 7.4 66.75 8.1 65.78 8 67.2 9.5 66.25 7.5 67.7 9.5 67.25 8.4 70 8.9 67.8 8.8 72 9.5 68 8.5 72.45 9 68.5 8.4 72.9 9.5

**Length Weight Length Weight**

*Number of children data collected according to the sex for the length and weight.*

comparison of an investigating dataset with a case control dataset. This is achieved through the visual evaluation of inconsistencies in children's growth pattern using

and dataset generated from Nsukka Medical Centre (NMC). These datasets are

WellGrowth adopts the average (50th percentile) score of WHO's children growth data for each month from 0 to 12 months in building WHO's growth curve. WHO's children growth data are gotten from children's empirical data such as height and weight at different stages of their growth for a sex matched reference. WellGrowth also integrates children growth data collected from the NMC. The average (50th percentile) score of the different children's weights and lengths in each month as curated from NMC are used to build the NMC/local growth curve. Finally, the individual growth curve is generated from inputs of a child's monthly weight/length as keyed into the WellGrowth input form by the WellGrowth App

stored in the WellGrowth App for further evaluation by the App users.

app enables the visualisation of inconsistent data through direct

(WHO) as the case control dataset

percentile of the data collected from NMC.

*The 50th percentile of data collected from NMC.*

the dataset from World Health Organisation8

<sup>7</sup> https://github.com/dora-png/growth-of-child

<sup>8</sup> https://www.who.int/toolkits/child-growth-standards/standards

**3.6 WellGrowth**

**Table 2.**

**Table 1.**

WellGrowth7

<sup>5</sup> https://github.com/marioJoker/Datax/tree/master/amazon-cell-phones-reviews

<sup>6</sup> https://www.who.int/toolkits/child-growth-standards/standards/length-height-for-age

*Visual Identification of Inconsistency in Pattern DOI: http://dx.doi.org/10.5772/intechopen.95506*


**Table 1.**

*Applications of Pattern Recognition*

update of the application.

**3.5 Case control method**

World Health Organisation6

length-height-for-age).

missingness in any discovered pattern.

reviewer that did not fill data in U, did not also fill data in X. The same observation holds for columns I and Z which have same distribution of missingness. The data analyst should make efforts to understand the relationships among the columns with joint and same distribution of missingness to present a robust report about the

Datax has also been used to evaluate cell phone reviews on the amazon online

tains 11 columns and 1,048,576 records. Datax was evaluated by a team of software developers in University of Nigeria, Nsukka and they described its efficiency in mining missing data and visualisation of associated patterns as excellent. Even so, it does not visualise the different forms of missing data. It specifically mines empty cells without noting representations such as "-", "not existing", "not available", among others as missing data. The authors hope to integrate this ability in the next

**3.4 Visual comparison of an investigated dataset with a case control dataset**

The visualisation of inconsistent data can be achieved through direct comparison of an investigating dataset with a case control dataset. Investigations that involve a comparison of an investigating dataset with a standard dataset are scenarios in which this approach can be used. This section of this chapter describes how WellGrowth app is used to enable the visual comparison of an investigated dataset with a case control dataset. It also describes the datasets investigated and

The case–control studies approach was used in comparing two datasets where one of the datasets is the case control while the other is the investigated dataset.

generated from Nsukka Medical Centre (NMC) is the investigated dataset. WHO data is gotten from children's empirical data which includes the length/height and weight of children at different stages of their growth for a sex matched reference. The weight and length of the children's data from WHO child growth standards for 0–12 months were used in investigating the NMC data. The average (50th percentile) score of the different children's weights and lengths in each month was used in the case control studies. This dataset is stored in WellGrowth app open source (see Section 3.22) for further analysis. The researchers collected the data (length for age and weight for age percentiles for girls and boys) directly from WHO web site (https://www.who.int/toolkits/child-growth-standards/standards/

NMC data are the weight and length of the children's growth data from 0 to 12 months for a sex matched references which are collected from the medical center Nsukka. The average (50th percentile) score of the different children's weights and lengths in each month as curated from NMC was used in the case control studies as the investigated dataset. This dataset is stored in WellGrowth app open source (see Section 3.22) for further analysis. The data collected from the NMC were not classified. So, the researcher classified them into different files according to the sex and the growth parameter per months from 0 to 12 months. The data were collected from NMC from May to august of 2020. **Table 1** presents a record of the number

<sup>5</sup> https://github.com/marioJoker/Datax/tree/master/amazon-cell-phones-reviews <sup>6</sup> https://www.who.int/toolkits/child-growth-standards/standards/length-height-for-age

(WHO) is the case control dataset and the dataset

how WellGrowth App was used in the investigation of the datasets.

. It con-

shopping store. The dataset is also deposited along Datax open source code5

**34**

*Number of children data collected according to the sex for the length and weight.*


**Table 2.**

*The 50th percentile of data collected from NMC.*

child's data collected by the researchers in NMC while **Table 2** presents the 50th percentile of the data collected from NMC.
