[Ikogor Clay]

Pls I need further help.

looking for a way to use "replace command" or any other possible way to change/correct age of individuals in relation to date of birth (DOB)

example: "replace age="20" if DOB=1999-01-23 for a range of date of births say Jan 1999 - October 1999.

Individuals born within this period should have same age, some may have been entered in error.

Also looking for a way to identify errors associated with wrong ages in relation to year of birth.

Example generated by -dataex-. To install: ssc install dataex

clear

input str19 NAME str10 DOB str2 AGE

"Eff Francis" "1999-07-24" "22"

"Koyo Bassey" "1999-08-13" "20"

"Rose Koyo" "1999-02-12" "21"

"Matt John" "1999-04-10" "20"

"Abigail christopher" "1999-04-08" "23"

"David Abel" "1999-04-21" "20"

"Chang Monica" "1999-07-06" "24"

"Chiche Augustine" "1999-09-06" "20"

"Enya Monica" "1999-01-08" "22"

"SARAH SAMUEL" "1999-09-19" "19"

Thanks

[Ikogor Clay]

input str19 NAME str10 DOB str2 AGE
"Eff Francis" "1999-07-24" "22"
"Koyo Bassey" "1999-08-13" "20"
"Rose Koyo" "1999-02-12" "21"
"Matt John" "1999-04-10" "20"
"Abigail christopher" "1999-04-08" "23"
"David Abel" "1999-04-21" "20"
"Chang Monica" "1999-07-06" "24"
"Chiche Augustine" "1999-09-06" "20"
"Enya Monica" "1999-01-08" "22"
"SARAH SAMUEL" "1999-09-19" "19"

Please I need further help; a command to identify errors associated with ages in relation to DOB as presented in data set above.
Individuals born within the same period should have same age but some may have been entered wrongly.
Secondly is there a command that can correct above errors? using a range of DOB
example, is it possible to use (replace age="20" if DOB=="1999-01-23") for a range of DOB say Jan 1999 - October 1999?

Thanks

[Ikogor Clay]

input str19 NAME str10 DOB str2 AGE
"Eff Francis" "1999-07-24" "22"
"Koyo Bassey" "1999-08-13" "20"
"Rose Koyo" "1999-02-12" "21"
"Matt John" "1999-04-10" "20"
"Abigail christopher" "1999-04-08" "23"
"David Abel" "1999-04-21" "20"
"Chang Monica" "1999-07-06" "24"
"Chiche Augustine" "1999-09-06" "20"
"Enya Monica" "1999-01-08" "22"
"SARAH SAMUEL" "1999-09-19" "19"

Please I need further help; a command to identify errors associated with ages in relation to DOB as presented in data set above.
Individuals born within the same period should have same age but some may have been entered wrongly.
Secondly is there a command that can correct above errors? using a range of DOB
example, is it possible to use (replace age="20" if DOB=="1999-01-23") for a range of DOB say Jan 1999 - October 1999?

Thanks

[Andrew Musau]

Based on the current date, this will give you monthly precision. You will need to extend the code to get actual date precision.

* Example generated by -dataex-. To install: ssc install dataex
clear
input str19 NAME str10 DOB str2 AGE
"Eff Francis"         "1999-07-24" "22"
"Koyo Bassey"         "1999-08-13" "20"
"Rose Koyo"           "1999-02-12" "21"
"Matt John"           "1999-04-10" "20"
"Abigail christopher" "1999-04-08" "23"
"David Abel"          "1999-04-21" "20"
"Chang Monica"        "1999-07-06" "24"
"Chiche Augustine"    "1999-09-06" "20"
"Enya Monica"         "1999-01-08" "22"
"SARAH SAMUEL"        "1999-09-19" "19"
end

gen dob= date(DOB, "YMD")
format dob %td
gen age= cond(month(dob)<= month(date("$S_DATE","DMY")),  year(date("$S_DATE","DMY"))- year(dob),  year(date("$S_DATE","DMY"))- year(dob)-1)

Res.:

. l, sep(10)

     +----------------------------------------------------------+
     |                NAME          DOB   AGE         dob   age |
     |----------------------------------------------------------|
  1. |         Eff Francis   1999-07-24    22   24jul1999    20 |
  2. |         Koyo Bassey   1999-08-13    20   13aug1999    20 |
  3. |           Rose Koyo   1999-02-12    21   12feb1999    20 |
  4. |           Matt John   1999-04-10    20   10apr1999    20 |
  5. | Abigail christopher   1999-04-08    23   08apr1999    20 |
  6. |          David Abel   1999-04-21    20   21apr1999    20 |
  7. |        Chang Monica   1999-07-06    24   06jul1999    20 |
  8. |    Chiche Augustine   1999-09-06    20   06sep1999    20 |
  9. |         Enya Monica   1999-01-08    22   08jan1999    20 |
 10. |        SARAH SAMUEL   1999-09-19    19   19sep1999    20 |
     +----------------------------------------------------------+

[Ikogor Clay]

input str19 NAME str10 DOB str2 AGE
"Eff Francis" "1999-07-24" "22"
"Koyo Bassey" "1999-08-13" "20"
"Rose Koyo" "1999-02-12" "21"
"Matt John" "1999-04-10" "20"
"Abigail christopher" "1999-04-08" "23"
"David Abel" "1999-04-21" "20"
"Chang Monica" "1999-07-06" "24"
"Chiche Augustine" "1999-09-06" "20"
"Enya Monica" "1999-01-08" "22"
"SARAH SAMUEL" "1999-09-19" "19"

[Andrew Musau]

Hi Ikogor, it is fine to ask for clarifications and additional advice, but do it here and not by sending private messages.

gen dob= date(DOB, "YMD")
format dob %td
gen age= cond(month(dob)<= month(date("$S_DATE","DMY")), year(date("$S_DATE","DMY"))- year(dob), year(date("$S_DATE","DMY"))- year(dob)-1)

Greetings Mr. Andrew, you sent the above syntax in response to my request to have uniform age for a range of dob. it worked very well, thank you very much.
Please I will be very grateful if you can help explain the concept so I can interpret and will be able to apply it in different ways.
Thanks again.

You can access the current date in Stata as follows:

. di "$S_DATE"
21 Oct 2019

Because above "21 Oct 2019" is a string, I can retrieve the current year and month using the month() and year() functions. See more about these functions in

help datetime

Therefore, I just specify a condition:

gen age= cond(month(dob)<= month(date("$S_DATE","DMY")), year(date("$S_DATE","DMY"))- year(dob), year(date("$S_DATE","DMY"))- year(dob)-1)

If month of birth is less than or equal to the current month (which means that your birthday this year has passed), then age is current year minus year of birth. Else, it is current year minus year of birth minus one. You only update your age on or once it is past your birthday.

The intention is actually to get exact age as at the time of data collection which was in September
Therefore individuals with birthdays before September or the date of data collection will be older than those with birthdays in November or after the date of data collection.

Now, to get the accurate age, we can specify an additional condition to the above. The code is ugly but very intuitive. Today is the 21st day of October, so we can add two observations of individuals whose birthdays are on the 20th (yesterday) and the 22nd (tomorrow).

* Example generated by -dataex-. To install: ssc install dataex
clear
input str19 NAME str10 DOB
"Eff Francis"         "1999-07-24"
"Koyo Bassey"         "1999-08-13"
"Rose Koyo"           "1999-02-12"
"Matt John"           "1999-04-10"
"Abigail christopher" "1999-04-08"
"David Abel"          "1999-04-21"
"Chang Monica"        "1999-07-06"
"Chiche Augustine"    "1999-09-06"
"Enya Monica"         "1999-01-08"
"SARAH SAMUEL"        "1999-09-19"
"XXX"                 "1999-10-20"
"XXX1"                "1999-10-22"
end

Now, all we need to do is to specify a separate condition for individuals whose birthdays are on the same month as the current month. Here, we now use the -day()- function, specifying that if the birthday is less than or equal to today (it means you have already celebrated your birthday or it's today), then age is current year minus year of birth. Else, it is current year minus year of birth minus one.

gen age= cond(month(dob)< month(date("$S_DATE","DMY")),  ///
year(date("$S_DATE","DMY"))- year(dob), cond(month(dob)== ///
month(date("$S_DATE","DMY"))& day(dob)<=day(date("$S_DATE","DMY")), ///
year(date("$S_DATE","DMY"))- year(dob),  year(date("$S_DATE","DMY"))- year(dob)-1))

Res.:

. l, sep(12)

     +----------------------------------------------------+
     |                NAME          DOB         dob   age |
     |----------------------------------------------------|
  1. |         Eff Francis   1999-07-24   24jul1999    20 |
  2. |         Koyo Bassey   1999-08-13   13aug1999    20 |
  3. |           Rose Koyo   1999-02-12   12feb1999    20 |
  4. |           Matt John   1999-04-10   10apr1999    20 |
  5. | Abigail christopher   1999-04-08   08apr1999    20 |
  6. |          David Abel   1999-04-21   21apr1999    20 |
  7. |        Chang Monica   1999-07-06   06jul1999    20 |
  8. |    Chiche Augustine   1999-09-06   06sep1999    20 |
  9. |         Enya Monica   1999-01-08   08jan1999    20 |
 10. |        SARAH SAMUEL   1999-09-19   19sep1999    20 |
 11. |                 XXX   1999-10-20   20oct1999    20 |
 12. |                XXX1   1999-10-22   22oct1999    19 |
     +----------------------------------------------------

[Ikogor Clay]

NAME	AGE
JOHN	23
EDEN	45
DONALD	18
HARRY	50
SARAH	30
TONY	17
BRIAN	37

kindly help with a syntax how to select persons with a set of age range.
Example ; I intend to select ONLY individuals with age ranging from 18 to 45.
Thanks.

[Andrew Musau]

gen tag= inrange(AGE, 18, 45)

See

help inrange()

[Ikogor Clay]

Thanks a lot, mr. Andrew

[Nick Cox]

Good that you got an answer, but a new question means a new thread, please.

[Ikogor Clay]

Thanks for all the support, please, i need help in sorting and extracting data for analysis.
i need to sort data of all individuals within the age of 4 to 28 years who are not enrolled in school and have no educational qualifications then compare marital status and nature of work of the heads of the household (Father/mother) in all these households were individuals are age 4-28 and not enrolled in school.
From the sample data set below, second column indicates code for enrollment in school, educational qualification, type of work and marital status.
Thank you for your help.

ref num	name	relationship	relationship code	gender	Age	enrolledinsch	enrollemen	eduqualification	eduqualification	typeofwork	typeofwork	maritalstatus	maritalstatus
Jon/home/1/01	John Gore	Head	1	male	56	0	not enrolled	3	second level qualification	2	self-employed	1	married
Jon/home/1/02	Susan Gore	Spouse	2	female	50	0	not enrolled	2	basic qualification	1	unemployed	1	married
Jon/home/1/03	George Gore	child	3	male	18	0	not enrolled	1	no qualification	1	unemployed	5	never married
Jon/home/1/04	Mark Gore	child	3	male	14	0	not enrolled	1	no qualification	1	unemployed	5	never married
Jon/home/1/05	Susan Gore	Grandchild	4	female	6	0	not enrolled	1	no qualification	3	dependent	5	never married
Mon/home/2/01	Linda Rober	Head	1	Female	30	0	not enrolled	1	basic qualification	1	unemployed	4	widowed
Mon/home/2/02	Mary Robert	child	3	female	9	0	not enrolled	1	no qualification	3	dependent	5	never married
Mon/home/2/03	David Robert	child	3	male	5	0	not enrolled	1	no qualification	3	dependent	5	never married
Can/arm/1/01	Fidel Joe	Head	1	male	44	0	not enrolled	3	basic qualification	1	unemployed	4	widowed
Can/arm/1/02	Okon Joe	child	3	male	8	0	not enrolled	1	no qualification	3	dependent	5	never married
Can/arm/1/03	Jane Joe	child	3	female	6	0	not enrolled	1	no qualification	3	dependent	5	never married
Can/arm/2/01	Martha David	Head	1	female	47	0	not enrolled	3	second level qualification	2	self-employed	3	divorced
Can/arm/2/02	Donald David	child	3	male	16	0	not enrolled	2	basic qualification	1	unemployed	5	never married
Can/arm/2/03	Gilda David	child	3	female	10	0	not enrolled	1	no qualification	3	dependent	5	never married
Can/arm/3/01	Lee Jon	Head	1	male	43	0	not enrolled	3	second level qualification	3	employee	1	married
Can/arm/3/02	Niki Jon	spouse	2	female	37	0	not enrolled	2	basic qualification	2	self-employed	1	married

[Clyde Schechter]

The above table cannot be an extract from your Stata data set because the variable name -ref num- is illegal, and it is also impossible to have two variables with the same name. (You show three such doublets). It is premature to ask for help with code if you have not yet imported your data into Stata.

Once you have done that, the helpful way to show example data is by using the -dataex- command. If you are running version 17, 16 or a fully updated version 15.1 or 14.2, -dataex- is already part of your official Stata installation. If not, run -ssc install dataex- to get it. Either way, run -help dataex- to read the simple instructions for using it. -dataex- will save you time; it is easier and quicker than typing out tables. It includes complete information about aspects of the data that are often critical to answering your question but cannot be seen from tabular displays or screenshots. It also makes it possible for those who want to help you to create a faithful representation of your example to try out their code, which in turn makes it more likely that their answer will actually work in your data.

i need to sort data of all individuals within the age of 4 to 28 years who are not enrolled in school and have no educational qualifications then compare marital status and nature of work of the heads of the household (Father/mother) in all these households were individuals are age 4-28 and not enrolled in school.

You need to clarify this. First, -sort- means putting things in numerical or alphabetical order, and doesn't seem relevant here. More important, are you really trying to compare those age 4-28 who are not enrolled in school and have no educational qualifications and compare their parents' marital status and nature of work, to those of the same age and not enrolled in school, irrespective of educational qualifications? This is a comparison of a part to a whole, which is generally not done in statistics because it raises complications of non-independence of observations; usually one compares a part to the complementary part. Or did you mistype what you want? Also, while in your example data all of the females are unemployed, if in your full data set both of some person's parents are employed and have different types of work, how do you want to handle that?

[Ikogor Clay]

Dear Clyde, thanks for your response, i created the table and typed it here like you rightly pointed out, i tried to relate it to my data set. However, here's another sample data using dataex
The "sort" being referred is not necessarily in numerical or alphabetical order but to extract or differentiate from the whole. What i mean is to extract data of all individual within age 4-28 who are not enrolled in school and have no educational qualification then compare the marital status of their parents/heads of households on one hand and also compare the nature of work of the parents/heads of households to see if there is a relationship with marital status(widowed,divorced,seperated,married, never married) of the parents and or the nature of work(employed,unemployed, self-employed, dependent) and why the individuals within school age are not enrolled in school. I hope this explanation is good enough to help. Thanks a lot.

* Example generated by -dataex-. To install: ssc install dataex
clear
input str31 hhmnsrrno str28 hhnsrrno str4 hhno byte hhsize str2 mno str25 m_name byte(sex relationship agey    maritalstatus b5labour    educationalqualification    currentlyenrolledinschl    chronicallyill)
"SS/CR/AKA/AKAM ISLAND/1/0001/01" "SS/CR/AKA/AKAM ISLAND/1/0001" "0001"  5 "01" "NDIFON NTUI NTUI"    1  1 20 5  6  6 0 0
"SS/CR/AKA/AKAM ISLAND/1/0001/02" "SS/CR/AKA/AKAM ISLAND/1/0001" "0001"  5 "02" "NDIFON NKOYO NTUI"    2 11 16 5 13  3 0 0
"SS/CR/AKA/AKAM ISLAND/1/0001/03" "SS/CR/AKA/AKAM ISLAND/1/0001" "0001"  5 "03" "EYANG OKPA ECHUR"    2 11 20 5  6  6 0 0
"SS/CR/AKA/AKAM ISLAND/1/0001/04" "SS/CR/AKA/AKAM ISLAND/1/0001" "0001"  5 "04" "NDIFON OMOM NTUI"    2 11 24 5  6  6 0 0
"SS/CR/AKA/AKAM ISLAND/1/0001/05" "SS/CR/AKA/AKAM ISLAND/1/0001" "0001"  5 "05" "NDIFON NTUI NDIFON"    1 11 26 5  6  1 0 0
"SS/CR/AKA/AKAM ISLAND/1/0002/01" "SS/CR/AKA/AKAM ISLAND/1/0002" "0002"  5 "01" "EJOR ALEX BONNIFACE"    1  1 25 1  6  6 0 0
"SS/CR/AKA/AKAM ISLAND/1/0002/02" "SS/CR/AKA/AKAM ISLAND/1/0002" "0002"  5 "02" "AMADU  EMMANUEL PATRICK"    1 11  6 5 13  1 0 0
"SS/CR/AKA/AKAM ISLAND/1/0002/03" "SS/CR/AKA/AKAM ISLAND/1/0002" "0002"  5 "03" "EYONG DAVID ESSIEN"    1  9  5 5  8  1 1 0
"SS/CR/AKA/AKAM ISLAND/1/0002/04" "SS/CR/AKA/AKAM ISLAND/1/0002" "0002"  5 "04" "OMIN VALENTINE EFFIONG"    1  9  6 5 13  1 0 0
"SS/CR/AKA/AKAM ISLAND/1/0002/05" "SS/CR/AKA/AKAM ISLAND/1/0002" "0002"  5 "05" "AMADU RUTH PATRICK"    2  9 15 5  8  2 1 0
"SS/CR/AKA/AKAM ISLAND/1/0003/01" "SS/CR/AKA/AKAM ISLAND/1/0003" "0003"  3 "01" "BASSEY GIFT BASSEY"    2  1 21 1  8  6 1 0
"SS/CR/AKA/AKAM ISLAND/1/0003/02" "SS/CR/AKA/AKAM ISLAND/1/0003" "0003"  3 "02" "DANIEL OKON EYO"    1 11  8 5  8  1 1 0
"SS/CR/AKA/AKAM ISLAND/1/0003/03" "SS/CR/AKA/AKAM ISLAND/1/0003" "0003"  3 "03" "OKON LAURA GODFREY"    2 11 20 5  6  6 0 0
"SS/CR/AKA/AKAM ISLAND/1/0004/01" "SS/CR/AKA/AKAM ISLAND/1/0004" "0004" 10 "01" "MBOTO ROSE ABENG"    2  1 54 4  6  1 0 0
"SS/CR/AKA/AKAM ISLAND/1/0004/02" "SS/CR/AKA/AKAM ISLAND/1/0004" "0004" 10 "02" "EDU DANIEL ENYA"    1 11 57 1  6 10 0 0
"SS/CR/AKA/AKAM ISLAND/1/0004/03" "SS/CR/AKA/AKAM ISLAND/1/0004" "0004" 10 "03" "MBOTO ABENG LAURA"    2  3 20 5  8  6 1 0
"SS/CR/AKA/AKAM ISLAND/1/0004/04" "SS/CR/AKA/AKAM ISLAND/1/0004" "0004" 10 "04" "MBOTO ABENG EMMANUEL"    1  3 11 5  8  1 1 0
"SS/CR/AKA/AKAM ISLAND/1/0004/05" "SS/CR/AKA/AKAM ISLAND/1/0004" "0004" 10 "05" "EDU PRECIOUS DANIEL"    2  3 13 5  8  2 1 0
"SS/CR/AKA/AKAM ISLAND/1/0004/06" "SS/CR/AKA/AKAM ISLAND/1/0004" "0004" 10 "06" "EDU THOMPSON DANIEL"    1  3 11 5  8  2 1 0
"SS/CR/AKA/AKAM ISLAND/1/0004/07" "SS/CR/AKA/AKAM ISLAND/1/0004" "0004" 10 "07" "ABENG MBOTO ALBERT"    1  3 28 5  6  6 0 1
"SS/CR/AKA/AKAM ISLAND/1/0004/08" "SS/CR/AKA/AKAM ISLAND/1/0004" "0004" 10 "08" "EDU GOODNESS DANIEL"    2  3 16 5  8  3 1 0
"SS/CR/AKA/AKAM ISLAND/1/0004/09" "SS/CR/AKA/AKAM ISLAND/1/0004" "0004" 10 "09" "EDU ENINI DANIEL"    1  3  7 5  8  1 1 0
"SS/CR/AKA/AKAM ISLAND/1/0004/10" "SS/CR/AKA/AKAM ISLAND/1/0004" "0004" 10 "10" "KELVIN DANIEL EDU"    1  3 17 5 13  3 0 0
"SS/CR/AKA/AKAM ISLAND/1/0005/01" "SS/CR/AKA/AKAM ISLAND/1/0005" "0005"  5 "01" "OGAR AGU THERESA"    2  1 60 4  6  1 0 0
"SS/CR/AKA/AKAM ISLAND/1/0005/02" "SS/CR/AKA/AKAM ISLAND/1/0005" "0005"  5 "02" "IKPEMBE MIRIAM EMMANUEL"    2  4  4 5  .  1 1 0
"SS/CR/AKA/AKAM ISLAND/1/0005/03" "SS/CR/AKA/AKAM ISLAND/1/0005" "0005"  5 "03" "IKPEMBE PROMISE EMMANUEL"    1  4 12 5  8  2 1 0
"SS/CR/AKA/AKAM ISLAND/1/0005/04" "SS/CR/AKA/AKAM ISLAND/1/0005" "0005"  5 "04" "IKPEMBE THOMAS EMMANUEL"    1  6 31 1  6  1 0 0
"SS/CR/AKA/AKAM ISLAND/1/0005/05" "SS/CR/AKA/AKAM ISLAND/1/0005" "0005"  5 "05" "RORIM KOKOMA EBANI"    2  6 26 1 12  1 0 0
"SS/CR/AKA/AKAM ISLAND/1/0006/01" "SS/CR/AKA/AKAM ISLAND/1/0006" "0006"  5 "01" "OJONG EMMANUELA OKORN"    2  1 47 4  6  6 0 0
"SS/CR/AKA/AKAM ISLAND/1/0006/02" "SS/CR/AKA/AKAM ISLAND/1/0006" "0006"  5 "02" "PAUL OKORN OJONG"    1  3 31 5  6  6 0 0
"SS/CR/AKA/AKAM ISLAND/1/0006/03" "SS/CR/AKA/AKAM ISLAND/1/0006" "0006"  5 "03" "VIVIAN OKORN OJONG"    2  3 35 1  6 12 0 0
"SS/CR/AKA/AKAM ISLAND/1/0006/04" "SS/CR/AKA/AKAM ISLAND/1/0006" "0006"  5 "04" "JENNIFER OKORN OJONG"    2  3 19 5  6  6 0 0
"SS/CR/AKA/AKAM ISLAND/1/0006/05" "SS/CR/AKA/AKAM ISLAND/1/0006" "0006"  5 "05" "VIOLET OKORN OJONG"    2  3 24 1  6  6 0 0
"SS/CR/AKA/AKAM ISLAND/1/0009/01" "SS/CR/AKA/AKAM ISLAND/1/0009" "0009"  8 "01" "ITA BASSEY VALENTINE"    2  1 50 4  6  2 0 0
"SS/CR/AKA/AKAM ISLAND/1/0009/02" "SS/CR/AKA/AKAM ISLAND/1/0009" "0009"  8 "02" "ITA SOLOMON VALENTINE"    1  3 13 5 13  2 0 0
"SS/CR/AKA/AKAM ISLAND/1/0009/03" "SS/CR/AKA/AKAM ISLAND/1/0009" "0009"  8 "03" "ITA NSIKAN GABRIEL"    2  3 35 1  6  1 0 0
"SS/CR/AKA/AKAM ISLAND/1/0009/04" "SS/CR/AKA/AKAM ISLAND/1/0009" "0009"  8 "04" "ITA EFFIONG VALENTINE"    1  3 14 5 13  2 0 0
"SS/CR/AKA/AKAM ISLAND/1/0009/05" "SS/CR/AKA/AKAM ISLAND/1/0009" "0009"  8 "05" "ITA CHRISTOPHER VALENTINE"    1  3 10 5 13  2 0 0
"SS/CR/AKA/AKAM ISLAND/1/0009/06" "SS/CR/AKA/AKAM ISLAND/1/0009" "0009"  8 "06" "ITA VALENTINE EKUBE"    1  3 16 5 13  2 0 0
"SS/CR/AKA/AKAM ISLAND/1/0009/07" "SS/CR/AKA/AKAM ISLAND/1/0009" "0009"  8 "07" "ITA GABRIEL MICHAEL"    1  4 17 5 13  3 0 0
"SS/CR/AKA/AKAM ISLAND/1/0009/08" "SS/CR/AKA/AKAM ISLAND/1/0009" "0009"  8 "08" "ITA ESTHER GABRIEL"    2  4 13 5  8  3 1 0
"SS/CR/CSG/AKANI/1/0015/01"       "SS/CR/CSG/AKANI/1/0015"       "0015"  3 "01" "EKPE EDAK ESSIEN"    2  1 45 2  6  2 0 0
"SS/CR/CSG/AKANI/1/0015/02"       "SS/CR/CSG/AKANI/1/0015"       "0015"  3 "02" "ABO CHARLES ETIM"    1  3 27 5  6  6 0 0
"SS/CR/CSG/AKANI/1/0015/03"       "SS/CR/CSG/AKANI/1/0015"       "0015"  3 "03" "ABO EMMANUEL ETIM"    1  3 29 5  6  6 0 0
"SS/CR/CSG/AKANI/1/0017/01"       "SS/CR/CSG/AKANI/1/0017"       "0017"  6 "01" "EBITO ANGELA EDET"    2  1 50 4  6  1 0 0
"SS/CR/CSG/AKANI/1/0017/02"       "SS/CR/CSG/AKANI/1/0017"       "0017"  6 "02" "EBITO JOSEPH EDET "    1  3 21 5  6  6 0 0
"SS/CR/CSG/AKANI/1/0017/03"       "SS/CR/CSG/AKANI/1/0017"       "0017"  6 "03" "EBITO IKWO EDET"    2  3 30 5  6  6 0 0
"SS/CR/CSG/AKANI/1/0017/04"       "SS/CR/CSG/AKANI/1/0017"       "0017"  6 "04" "EBITO NKOYO EDET"    2  3 32 5  6  6 0 0
"SS/CR/CSG/AKANI/1/0017/05"       "SS/CR/CSG/AKANI/1/0017"       "0017"  6 "05" "FRED JOSEPH AYASA "    1  4  9 5  8  1 1 0
"SS/CR/CSG/AKANI/1/0017/06"       "SS/CR/CSG/AKANI/1/0017"       "0017"  6 "06" "EBITAGHA SAVIOUR "    1  4 19 5  6  6 0 0
"SS/CR/CSG/AKANI/1/0019/01"       "SS/CR/CSG/AKANI/1/0019"       "0019"  7 "01" "EWA EMMANUEL EFFIOM"    1  1 39 2  6  2 0 0
"SS/CR/CSG/AKANI/1/0019/02"       "SS/CR/CSG/AKANI/1/0019"       "0019"  7 "02" "PETER MERCY"    2 10 35 5  6  1 0 0
"SS/CR/CSG/AKANI/1/0019/03"       "SS/CR/CSG/AKANI/1/0019"       "0019"  7 "03" "EWA GLORY"    2 10  2 5  .  1 0 0
"SS/CR/CSG/AKANI/1/0019/04"       "SS/CR/CSG/AKANI/1/0019"       "0019"  7 "04" "EWA MARGARET"    2 10  6 5  8  1 1 0
"SS/CR/CSG/AKANI/1/0019/05"       "SS/CR/CSG/AKANI/1/0019"       "0019"  7 "05" "EFFIOM LINDA EMMANUEL"    2  3  8 5  8  1 1 0
"SS/CR/CSG/AKANI/1/0019/06"       "SS/CR/CSG/AKANI/1/0019"       "0019"  7 "06" "EFFIOM EMMANULLA EMMANUEL"    2  3 10 5  8  1 1 0
"SS/CR/CSG/AKANI/1/0019/07"       "SS/CR/CSG/AKANI/1/0019"       "0019"  7 "07" "IJUMA ISAIAH CHRISTIAN"    1  3  5 5  8  1 1 0
"SS/CR/CSG/AKANI/1/0020/01"       "SS/CR/CSG/AKANI/1/0020"       "0020"  4 "01" "NSA ELIZABETH EYO"    2  1 45 4  6  6 0 0
"SS/CR/CSG/AKANI/1/0020/02"       "SS/CR/CSG/AKANI/1/0020"       "0020"  4 "02" "NSA MARY EYO"    2 11 39 5  6  9 0 0
"SS/CR/CSG/AKANI/1/0020/03"       "SS/CR/CSG/AKANI/1/0020"       "0020"  4 "03" "OKON EKANEM EYO"    2  3 27 5  6  6 0 0
"SS/CR/CSG/AKANI/1/0020/04"       "SS/CR/CSG/AKANI/1/0020"       "0020"  4 "04" "NSA GLORY EYO"    2  3 17 5 13  2 0 0
"SS/CR/IKM/BOGHA/2/0034/01"       "SS/CR/IKM/BOGHA/2/0034"       "0034"  8 "01" "EYAM DARLINGTON NKWAM"    1  1 40 1  4  2 0 0
"SS/CR/IKM/BOGHA/2/0034/02"       "SS/CR/IKM/BOGHA/2/0034"       "0034"  8 "02" "NKWAM OGBINA"    2 11 21 5  2  2 0 0
"SS/CR/IKM/BOGHA/2/0034/03"       "SS/CR/IKM/BOGHA/2/0034"       "0034"  8 "03" "NKWAM ENDURANCE"    2 11 19 5  6  3 0 0
"SS/CR/IKM/BOGHA/2/0034/04"       "SS/CR/IKM/BOGHA/2/0034"       "0034"  8 "04" "NKWAM MERCY"    2 11 17 5 12  2 0 0
"SS/CR/IKM/BOGHA/2/0034/05"       "SS/CR/IKM/BOGHA/2/0034"       "0034"  8 "05" "NKWAM MARCUS"    1 11 42 1 13  3 0 0
"SS/CR/IKM/BOGHA/2/0034/06"       "SS/CR/IKM/BOGHA/2/0034"       "0034"  8 "06" "NKWAM ANGELA"    2  2 37 1  4  2 0 0
"SS/CR/IKM/BOGHA/2/0034/07"       "SS/CR/IKM/BOGHA/2/0034"       "0034"  8 "07" "NKWAM VICTORY"    1  3  9 5  8  1 1 0
"SS/CR/IKM/BOGHA/2/0034/08"       "SS/CR/IKM/BOGHA/2/0034"       "0034"  8 "08" "NKWAM WINNER"    2  3  5 5  8  1 1 0
"SS/CR/IKM/BOGHA/2/0040/01"       "SS/CR/IKM/BOGHA/2/0040"       "0040"  4 "01" "ODIGHA LIVINUS "    1  1 69 2 13  1 0 0
"SS/CR/IKM/BOGHA/2/0040/02"       "SS/CR/IKM/BOGHA/2/0040"       "0040"  4 "02" "ENONO KINGSLEY ODIGHA"    1  3 34 5  6  1 0 0
"SS/CR/IKM/BOGHA/2/0040/03"       "SS/CR/IKM/BOGHA/2/0040"       "0040"  4 "03" "ODIGHA ETITAH"    2  3 24 5  6  1 0 0
"SS/CR/IKM/BOGHA/2/0040/04"       "SS/CR/IKM/BOGHA/2/0040"       "0040"  4 "04" "ODIGHA OGONYI"    2  3 29 5  6  1 0 0
end

[Ikogor Clay]

Dear Clyde, thanks for your response, i created the table and typed it here like you rightly pointed out, i tried to relate it to my data set. However, here's another sample data generated using dataex.
The "sort" being referred is not necessarily in numerical or alphabetical order but to extract or differentiate from the whole. What i mean is to extract data of all individual within age 4-28 who are not enrolled in school and have no educational qualification then compare the marital status of their parents/heads of households on one hand and also compare the nature of work of the parents/heads of households to see if there is a relationship with marital status(widowed,divorced,seperated,married, never married) of the parents and or the nature of work(employed,unemployed, self-employed, dependent) and why the individuals within school age are not enrolled in school. I hope this explanation is good enough to help. Thanks a lot.

* Example generated by -dataex-. To install: ssc install dataex
clear
input str31 hhmnsrrno str28 hhnsrrno str4 hhno byte hhsize str2 mno str25 m_name str1 sex str2 relationship    byte agey str1 maritalstatus str2(b5labour    educationalqualification)    str1(currentlyenrolledinschl    chronicallyill)
"SS/CR/AKA/AKAM ISLAND/1/0001/01" "SS/CR/AKA/AKAM ISLAND/1/0001" "0001"  5 "01" "NDIFON NTUI NTUI"    "1" "1"  20 "5" "6"  "6"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0001/02" "SS/CR/AKA/AKAM ISLAND/1/0001" "0001"  5 "02" "NDIFON NKOYO NTUI"    "2" "11" 16 "5" "13" "3"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0001/03" "SS/CR/AKA/AKAM ISLAND/1/0001" "0001"  5 "03" "EYANG OKPA ECHUR"    "2" "11" 20 "5" "6"  "6"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0001/04" "SS/CR/AKA/AKAM ISLAND/1/0001" "0001"  5 "04" "NDIFON OMOM NTUI"    "2" "11" 24 "5" "6"  "6"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0001/05" "SS/CR/AKA/AKAM ISLAND/1/0001" "0001"  5 "05" "NDIFON NTUI NDIFON"    "1" "11" 26 "5" "6"  "1"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0002/01" "SS/CR/AKA/AKAM ISLAND/1/0002" "0002"  5 "01" "EJOR ALEX BONNIFACE"    "1" "1"  25 "1" "6"  "6"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0002/02" "SS/CR/AKA/AKAM ISLAND/1/0002" "0002"  5 "02" "AMADU  EMMANUEL PATRICK"    "1" "11"  6 "5" "13" "1"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0002/03" "SS/CR/AKA/AKAM ISLAND/1/0002" "0002"  5 "03" "EYONG DAVID ESSIEN"    "1" "9"   5 "5" "8"  "1"  "1" "0"
"SS/CR/AKA/AKAM ISLAND/1/0002/04" "SS/CR/AKA/AKAM ISLAND/1/0002" "0002"  5 "04" "OMIN VALENTINE EFFIONG"    "1" "9"   6 "5" "13" "1"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0002/05" "SS/CR/AKA/AKAM ISLAND/1/0002" "0002"  5 "05" "AMADU RUTH PATRICK"    "2" "9"  15 "5" "8"  "2"  "1" "0"
"SS/CR/AKA/AKAM ISLAND/1/0003/01" "SS/CR/AKA/AKAM ISLAND/1/0003" "0003"  3 "01" "BASSEY GIFT BASSEY"    "2" "1"  21 "1" "8"  "6"  "1" "0"
"SS/CR/AKA/AKAM ISLAND/1/0003/02" "SS/CR/AKA/AKAM ISLAND/1/0003" "0003"  3 "02" "DANIEL OKON EYO"    "1" "11"  8 "5" "8"  "1"  "1" "0"
"SS/CR/AKA/AKAM ISLAND/1/0003/03" "SS/CR/AKA/AKAM ISLAND/1/0003" "0003"  3 "03" "OKON LAURA GODFREY"    "2" "11" 20 "5" "6"  "6"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0004/01" "SS/CR/AKA/AKAM ISLAND/1/0004" "0004" 10 "01" "MBOTO ROSE ABENG"    "2" "1"  54 "4" "6"  "1"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0004/02" "SS/CR/AKA/AKAM ISLAND/1/0004" "0004" 10 "02" "EDU DANIEL ENYA"    "1" "11" 57 "1" "6"  "10" "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0004/03" "SS/CR/AKA/AKAM ISLAND/1/0004" "0004" 10 "03" "MBOTO ABENG LAURA"    "2" "3"  20 "5" "8"  "6"  "1" "0"
"SS/CR/AKA/AKAM ISLAND/1/0004/04" "SS/CR/AKA/AKAM ISLAND/1/0004" "0004" 10 "04" "MBOTO ABENG EMMANUEL"    "1" "3"  11 "5" "8"  "1"  "1" "0"
"SS/CR/AKA/AKAM ISLAND/1/0004/05" "SS/CR/AKA/AKAM ISLAND/1/0004" "0004" 10 "05" "EDU PRECIOUS DANIEL"    "2" "3"  13 "5" "8"  "2"  "1" "0"
"SS/CR/AKA/AKAM ISLAND/1/0004/06" "SS/CR/AKA/AKAM ISLAND/1/0004" "0004" 10 "06" "EDU THOMPSON DANIEL"    "1" "3"  11 "5" "8"  "2"  "1" "0"
"SS/CR/AKA/AKAM ISLAND/1/0004/07" "SS/CR/AKA/AKAM ISLAND/1/0004" "0004" 10 "07" "ABENG MBOTO ALBERT"    "1" "3"  28 "5" "6"  "6"  "0" "1"
"SS/CR/AKA/AKAM ISLAND/1/0004/08" "SS/CR/AKA/AKAM ISLAND/1/0004" "0004" 10 "08" "EDU GOODNESS DANIEL"    "2" "3"  16 "5" "8"  "3"  "1" "0"
"SS/CR/AKA/AKAM ISLAND/1/0004/09" "SS/CR/AKA/AKAM ISLAND/1/0004" "0004" 10 "09" "EDU ENINI DANIEL"    "1" "3"   7 "5" "8"  "1"  "1" "0"
"SS/CR/AKA/AKAM ISLAND/1/0004/10" "SS/CR/AKA/AKAM ISLAND/1/0004" "0004" 10 "10" "KELVIN DANIEL EDU"    "1" "3"  17 "5" "13" "3"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0005/01" "SS/CR/AKA/AKAM ISLAND/1/0005" "0005"  5 "01" "OGAR AGU THERESA"    "2" "1"  60 "4" "6"  "1"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0005/02" "SS/CR/AKA/AKAM ISLAND/1/0005" "0005"  5 "02" "IKPEMBE MIRIAM EMMANUEL"    "2" "4"   4 "5" ""   "1"  "1" "0"
"SS/CR/AKA/AKAM ISLAND/1/0005/03" "SS/CR/AKA/AKAM ISLAND/1/0005" "0005"  5 "03" "IKPEMBE PROMISE EMMANUEL"    "1" "4"  12 "5" "8"  "2"  "1" "0"
"SS/CR/AKA/AKAM ISLAND/1/0005/04" "SS/CR/AKA/AKAM ISLAND/1/0005" "0005"  5 "04" "IKPEMBE THOMAS EMMANUEL"    "1" "6"  31 "1" "6"  "1"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0005/05" "SS/CR/AKA/AKAM ISLAND/1/0005" "0005"  5 "05" "RORIM KOKOMA EBANI"    "2" "6"  26 "1" "12" "1"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0006/01" "SS/CR/AKA/AKAM ISLAND/1/0006" "0006"  5 "01" "OJONG EMMANUELA OKORN"    "2" "1"  47 "4" "6"  "6"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0006/02" "SS/CR/AKA/AKAM ISLAND/1/0006" "0006"  5 "02" "PAUL OKORN OJONG"    "1" "3"  31 "5" "6"  "6"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0006/03" "SS/CR/AKA/AKAM ISLAND/1/0006" "0006"  5 "03" "VIVIAN OKORN OJONG"    "2" "3"  35 "1" "6"  "12" "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0006/04" "SS/CR/AKA/AKAM ISLAND/1/0006" "0006"  5 "04" "JENNIFER OKORN OJONG"    "2" "3"  19 "5" "6"  "6"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0006/05" "SS/CR/AKA/AKAM ISLAND/1/0006" "0006"  5 "05" "VIOLET OKORN OJONG"    "2" "3"  24 "1" "6"  "6"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0009/01" "SS/CR/AKA/AKAM ISLAND/1/0009" "0009"  8 "01" "ITA BASSEY VALENTINE"    "2" "1"  50 "4" "6"  "2"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0009/02" "SS/CR/AKA/AKAM ISLAND/1/0009" "0009"  8 "02" "ITA SOLOMON VALENTINE"    "1" "3"  13 "5" "13" "2"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0009/03" "SS/CR/AKA/AKAM ISLAND/1/0009" "0009"  8 "03" "ITA NSIKAN GABRIEL"    "2" "3"  35 "1" "6"  "1"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0009/04" "SS/CR/AKA/AKAM ISLAND/1/0009" "0009"  8 "04" "ITA EFFIONG VALENTINE"    "1" "3"  14 "5" "13" "2"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0009/05" "SS/CR/AKA/AKAM ISLAND/1/0009" "0009"  8 "05" "ITA CHRISTOPHER VALENTINE"    "1" "3"  10 "5" "13" "2"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0009/06" "SS/CR/AKA/AKAM ISLAND/1/0009" "0009"  8 "06" "ITA VALENTINE EKUBE"    "1" "3"  16 "5" "13" "2"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0009/07" "SS/CR/AKA/AKAM ISLAND/1/0009" "0009"  8 "07" "ITA GABRIEL MICHAEL"    "1" "4"  17 "5" "13" "3"  "0" "0"
"SS/CR/AKA/AKAM ISLAND/1/0009/08" "SS/CR/AKA/AKAM ISLAND/1/0009" "0009"  8 "08" "ITA ESTHER GABRIEL"    "2" "4"  13 "5" "8"  "3"  "1" "0"
"SS/CR/CSG/AKANI/1/0015/01"       "SS/CR/CSG/AKANI/1/0015"       "0015"  3 "01" "EKPE EDAK ESSIEN"    "2" "1"  45 "2" "6"  "2"  "0" "0"
"SS/CR/CSG/AKANI/1/0015/02"       "SS/CR/CSG/AKANI/1/0015"       "0015"  3 "02" "ABO CHARLES ETIM"    "1" "3"  27 "5" "6"  "6"  "0" "0"
"SS/CR/CSG/AKANI/1/0015/03"       "SS/CR/CSG/AKANI/1/0015"       "0015"  3 "03" "ABO EMMANUEL ETIM"    "1" "3"  29 "5" "6"  "6"  "0" "0"
"SS/CR/CSG/AKANI/1/0017/01"       "SS/CR/CSG/AKANI/1/0017"       "0017"  6 "01" "EBITO ANGELA EDET"    "2" "1"  50 "4" "6"  "1"  "0" "0"
"SS/CR/CSG/AKANI/1/0017/02"       "SS/CR/CSG/AKANI/1/0017"       "0017"  6 "02" "EBITO JOSEPH EDET "    "1" "3"  21 "5" "6"  "6"  "0" "0"
"SS/CR/CSG/AKANI/1/0017/03"       "SS/CR/CSG/AKANI/1/0017"       "0017"  6 "03" "EBITO IKWO EDET"    "2" "3"  30 "5" "6"  "6"  "0" "0"
"SS/CR/CSG/AKANI/1/0017/04"       "SS/CR/CSG/AKANI/1/0017"       "0017"  6 "04" "EBITO NKOYO EDET"    "2" "3"  32 "5" "6"  "6"  "0" "0"
"SS/CR/CSG/AKANI/1/0017/05"       "SS/CR/CSG/AKANI/1/0017"       "0017"  6 "05" "FRED JOSEPH AYASA "    "1" "4"   9 "5" "8"  "1"  "1" "0"
"SS/CR/CSG/AKANI/1/0017/06"       "SS/CR/CSG/AKANI/1/0017"       "0017"  6 "06" "EBITAGHA SAVIOUR "    "1" "4"  19 "5" "6"  "6"  "0" "0"
"SS/CR/CSG/AKANI/1/0019/01"       "SS/CR/CSG/AKANI/1/0019"       "0019"  7 "01" "EWA EMMANUEL EFFIOM"    "1" "1"  39 "2" "6"  "2"  "0" "0"
"SS/CR/CSG/AKANI/1/0019/02"       "SS/CR/CSG/AKANI/1/0019"       "0019"  7 "02" "PETER MERCY"    "2" "10" 35 "5" "6"  "1"  "0" "0"
"SS/CR/CSG/AKANI/1/0019/03"       "SS/CR/CSG/AKANI/1/0019"       "0019"  7 "03" "EWA GLORY"    "2" "10"  2 "5" ""   "1"  "0" "0"
"SS/CR/CSG/AKANI/1/0019/04"       "SS/CR/CSG/AKANI/1/0019"       "0019"  7 "04" "EWA MARGARET"    "2" "10"  6 "5" "8"  "1"  "1" "0"
"SS/CR/CSG/AKANI/1/0019/05"       "SS/CR/CSG/AKANI/1/0019"       "0019"  7 "05" "EFFIOM LINDA EMMANUEL"    "2" "3"   8 "5" "8"  "1"  "1" "0"
"SS/CR/CSG/AKANI/1/0019/06"       "SS/CR/CSG/AKANI/1/0019"       "0019"  7 "06" "EFFIOM EMMANULLA EMMANUEL"    "2" "3"  10 "5" "8"  "1"  "1" "0"
"SS/CR/CSG/AKANI/1/0019/07"       "SS/CR/CSG/AKANI/1/0019"       "0019"  7 "07" "IJUMA ISAIAH CHRISTIAN"    "1" "3"   5 "5" "8"  "1"  "1" "0"
"SS/CR/CSG/AKANI/1/0020/01"       "SS/CR/CSG/AKANI/1/0020"       "0020"  4 "01" "NSA ELIZABETH EYO"    "2" "1"  45 "4" "6"  "6"  "0" "0"
"SS/CR/CSG/AKANI/1/0020/02"       "SS/CR/CSG/AKANI/1/0020"       "0020"  4 "02" "NSA MARY EYO"    "2" "11" 39 "5" "6"  "9"  "0" "0"
"SS/CR/CSG/AKANI/1/0020/03"       "SS/CR/CSG/AKANI/1/0020"       "0020"  4 "03" "OKON EKANEM EYO"    "2" "3"  27 "5" "6"  "6"  "0" "0"
"SS/CR/CSG/AKANI/1/0020/04"       "SS/CR/CSG/AKANI/1/0020"       "0020"  4 "04" "NSA GLORY EYO"    "2" "3"  17 "5" "13" "2"  "0" "0"
"SS/CR/IKM/BOGHA/2/0034/01"       "SS/CR/IKM/BOGHA/2/0034"       "0034"  8 "01" "EYAM DARLINGTON NKWAM"    "1" "1"  40 "1" "4"  "2"  "0" "0"
"SS/CR/IKM/BOGHA/2/0034/02"       "SS/CR/IKM/BOGHA/2/0034"       "0034"  8 "02" "NKWAM OGBINA"    "2" "11" 21 "5" "2"  "2"  "0" "0"
"SS/CR/IKM/BOGHA/2/0034/03"       "SS/CR/IKM/BOGHA/2/0034"       "0034"  8 "03" "NKWAM ENDURANCE"    "2" "11" 19 "5" "6"  "3"  "0" "0"
"SS/CR/IKM/BOGHA/2/0034/04"       "SS/CR/IKM/BOGHA/2/0034"       "0034"  8 "04" "NKWAM MERCY"    "2" "11" 17 "5" "12" "2"  "0" "0"
"SS/CR/IKM/BOGHA/2/0034/05"       "SS/CR/IKM/BOGHA/2/0034"       "0034"  8 "05" "NKWAM MARCUS"    "1" "11" 42 "1" "13" "3"  "0" "0"
"SS/CR/IKM/BOGHA/2/0034/06"       "SS/CR/IKM/BOGHA/2/0034"       "0034"  8 "06" "NKWAM ANGELA"    "2" "2"  37 "1" "4"  "2"  "0" "0"
"SS/CR/IKM/BOGHA/2/0034/07"       "SS/CR/IKM/BOGHA/2/0034"       "0034"  8 "07" "NKWAM VICTORY"    "1" "3"   9 "5" "8"  "1"  "1" "0"
"SS/CR/IKM/BOGHA/2/0034/08"       "SS/CR/IKM/BOGHA/2/0034"       "0034"  8 "08" "NKWAM WINNER"    "2" "3"   5 "5" "8"  "1"  "1" "0"
"SS/CR/IKM/BOGHA/2/0040/01"       "SS/CR/IKM/BOGHA/2/0040"       "0040"  4 "01" "ODIGHA LIVINUS "    "1" "1"  69 "2" "13" "1"  "0" "0"
"SS/CR/IKM/BOGHA/2/0040/02"       "SS/CR/IKM/BOGHA/2/0040"       "0040"  4 "02" "ENONO KINGSLEY ODIGHA"    "1" "3"  34 "5" "6"  "1"  "0" "0"
"SS/CR/IKM/BOGHA/2/0040/03"       "SS/CR/IKM/BOGHA/2/0040"       "0040"  4 "03" "ODIGHA ETITAH"    "2" "3"  24 "5" "6"  "1"  "0" "0"
"SS/CR/IKM/BOGHA/2/0040/04"       "SS/CR/IKM/BOGHA/2/0040"       "0040"  4 "04" "ODIGHA OGONYI"    "2" "3"  29 "5" "6"  "1"  "0" "0"
end

[Ikogor Clay]

"hhmnsrrno" (household member refnum) is unique reference for each individual household member while
"hhnsrrn"(household ref num) is unique reference for each household.