Home » Topics » Fertility » Contraceptive calendar in Nigeria 2013 dataset
| Contraceptive calendar in Nigeria 2013 dataset [message #6788] |
Wed, 15 July 2015 16:34  |
ccox
Messages: 6
Registered: March 2013
Location: St. Paul, MN
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Member |
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Dear DHS,
I am working with a few colleagues on an analysis that will utilize data from the contraceptive calendar in the Nigeria 2013 dataset. We are running into a few issues and hope to get some guidance.
1. In the recode manual, it states that the calendar data are stored as single variables of 80 characters. In the Nigeria 2013 dataset, it appears that there are only 67 characters. Is this correct?
2. Our next question refers to vcal_1. It is my understanding that the earliest positions in the string variable relate to the most recent times and the end of the string relates to further back in time. When we use the code below to destring the variable we find that the last positions for some respondents are blank. It is my understanding that the blank positions correspond to the months after the month of the interview, thus shouldn't the blanks appear in the first positions because they would be the most recent times?
3. Our next question refers to vcal_2. When we use the code below to destring vcal_2, we find that when a respondent provides a reason for contraceptive discontinuation it appears in the 1st position regardless of when the respondent actually discontinued the contraceptive method. I would expect that the reason for discontinuation would be entered in the position that corresponds to the date of discontinuation from vcal_1. Is our code below used to destring vcal_2 incorrect?
4. Our last question refers to vcal_3, which according to the recode manual is the column that records episodes of marriage. Does the Nigeria 2013 dataset include vcal_3? If so, is the variable called something else? We can't seem to find it in the dataset.
Code for questions 2 and 3:
format %67s vcal_1
gen cal1 = substr(vcal_1,1,1)
gen cal2 = substr(vcal_1,2,1)
gen cal3 = substr(vcal_1,3,1)
gen cal4 = substr(vcal_1,4,1)...
gen cal67 = substr(vcal_1,67,1)
format %67s vcal_2
gen discal1 = substr(vcal_2,1,1)
gen discal2 = substr(vcal_2,2,1)
gen discal3 = substr(vcal_2,3,1)
gen discal4 = substr(vcal_2,4,1)...
gen discal67 = substr(vcal_2,67,1)
reshape long cal discal, i(caseid) j(event_time)
Thank you very much for your assistance!
Sincerely,
Carie
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| Re: Contraceptive calendar in Nigeria 2013 dataset [message #6841 is a reply to message #6788] |
Tue, 21 July 2015 09:41  |
Liz-DHS
Messages: 1516
Registered: February 2013
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Senior Member |
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Dear User,
Here is a response from one of our data processing staff, Mianmian Yu. Her responses are in bold.
1. In the recode manual, it states that the calendar data are stored as single variables of 80 characters. In the Nigeria 2013 dataset, it appears that there are only 67 characters. Is this correct? '80 characters' means the maximum length of the calendar variables. The factual number of characters that appear in the variables depends on the month and year of interview.
2. Our next question refers to vcal_1. It is my understanding that the earliest positions in the string variable relate to the most recent times and the end of the string relates to further back in time. When we use the code below to destring the variable we find that the last positions for some respondents are blank. It is my understanding that the blank positions correspond to the months after the month of the interview, thus shouldn't the blanks appear in the first positions because they would be the most recent times? Spaces for the months after the interview month must be blank because the survey was finished before then. The first non-blank position should represent the most recent status of contraceptive use.
3. Our next question refers to vcal_2. When we use the code below to destring vcal_2, we find that when a respondent provides a reason for contraceptive discontinuation it appears in the 1st position regardless of when the respondent actually discontinued the contraceptive method. I would expect that the reason for discontinuation would be entered in the position that corresponds to the date of discontinuation from vcal_1. Is our code below used to destring vcal_2 incorrect? The reason for discontinuation is recorded at the month where a contraceptive method is switched off. If there appears to be an exceptional case, please let us know its ID ( cluster #, HH# and line # ) and we will be happy to investigate it.
4. Our last question refers to vcal_3, which according to the recode manual is the column that records episodes of marriage. Does the Nigeria 2013 dataset include vcal_3? If so, is the variable called something else? We can't seem to find it in the dataset. Marriage status was not asked in the calendar of Nigeria DHS 2013.
If you have additional questions, please feel free to post again.
Thank you!
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| Re: Contraceptive calendar in Nigeria 2013 dataset [message #6884 is a reply to message #6841] |
Mon, 27 July 2015 17:02 |
ccox
Messages: 6
Registered: March 2013
Location: St. Paul, MN
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Member |
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Dear Mianmian Yu,
Thank you very much for your response to our questions. We have a few follow-up questions to two of your responses.
1. ORIGINAL QUESTION: Our next question refers to vcal_1. It is my understanding that the earliest positions in the string variable relate to the most recent times and the end of the string relates to further back in time. When we use the code below to destring the variable we find that the last positions for some respondents are blank. It is my understanding that the blank positions correspond to the months after the month of the interview, thus shouldn't the blanks appear in the first positions because they would be the most recent times?
DHS FORUM RESPONSE: Spaces for the months after the interview month must be blank because the survey was finished before then. The first non-blank position should represent the most recent status of contraceptive use.
FOLLOW-UP QUESTION: Why do the blank positions (months after the interview) appear in the last positions (furthest in time) in the Nigeria 2013 dataset (Stata code provided below)? Since the blank positions represent months after the interview (thus more recent in time), shouldn't they come before the first non-blank positions?
format %67s vcal_1
gen cal1 = substr(vcal_1,1,1)
gen cal2 = substr(vcal_1,2,1)
gen cal3 = substr(vcal_1,3,1)
gen cal4 = substr(vcal_1,4,1)
gen cal5 = substr(vcal_1,5,1)
gen cal6 = substr(vcal_1,6,1)
gen cal7 = substr(vcal_1,7,1)
gen cal8 = substr(vcal_1,8,1)
gen cal9 = substr(vcal_1,9,1)
gen cal10 = substr(vcal_1,10,1)
gen cal11 = substr(vcal_1,11,1)
gen cal12 = substr(vcal_1,12,1)
gen cal13 = substr(vcal_1,13,1)
gen cal14 = substr(vcal_1,14,1)
gen cal15 = substr(vcal_1,15,1)
gen cal16 = substr(vcal_1,16,1)
gen cal17 = substr(vcal_1,17,1)
gen cal18 = substr(vcal_1,18,1)
gen cal19 = substr(vcal_1,19,1)
gen cal20 = substr(vcal_1,20,1)
gen cal21 = substr(vcal_1,21,1)
gen cal22 = substr(vcal_1,22,1)
gen cal23 = substr(vcal_1,23,1)
gen cal24 = substr(vcal_1,24,1)
gen cal25 = substr(vcal_1,25,1)
gen cal26 = substr(vcal_1,26,1)
gen cal27 = substr(vcal_1,27,1)
gen cal28 = substr(vcal_1,28,1)
gen cal29 = substr(vcal_1,29,1)
gen cal30 = substr(vcal_1,30,1)
gen cal31 = substr(vcal_1,31,1)
gen cal32 = substr(vcal_1,32,1)
gen cal33 = substr(vcal_1,33,1)
gen cal34 = substr(vcal_1,34,1)
gen cal35 = substr(vcal_1,35,1)
gen cal36 = substr(vcal_1,36,1)
gen cal37 = substr(vcal_1,37,1)
gen cal38 = substr(vcal_1,38,1)
gen cal39 = substr(vcal_1,39,1)
gen cal40 = substr(vcal_1,40,1)
gen cal41 = substr(vcal_1,41,1)
gen cal42 = substr(vcal_1,42,1)
gen cal43 = substr(vcal_1,43,1)
gen cal44 = substr(vcal_1,44,1)
gen cal45 = substr(vcal_1,45,1)
gen cal46 = substr(vcal_1,46,1)
gen cal47 = substr(vcal_1,47,1)
gen cal48 = substr(vcal_1,48,1)
gen cal49 = substr(vcal_1,49,1)
gen cal50 = substr(vcal_1,50,1)
gen cal51 = substr(vcal_1,51,1)
gen cal52 = substr(vcal_1,52,1)
gen cal53 = substr(vcal_1,53,1)
gen cal54 = substr(vcal_1,54,1)
gen cal55 = substr(vcal_1,55,1)
gen cal56 = substr(vcal_1,56,1)
gen cal57 = substr(vcal_1,57,1)
gen cal58 = substr(vcal_1,58,1)
gen cal59 = substr(vcal_1,59,1)
gen cal60 = substr(vcal_1,60,1)
gen cal61 = substr(vcal_1,61,1)
gen cal62 = substr(vcal_1,62,1)
gen cal63 = substr(vcal_1,63,1)
gen cal64 = substr(vcal_1,64,1)
gen cal65 = substr(vcal_1,65,1)
gen cal66 = substr(vcal_1,66,1)
gen cal67 = substr(vcal_1,67,1)
reshape long cal, i(caseid) j(event_time)
2. ORIGINAL QUESTION: Our next question refers to vcal_2. When we use the code below to destring vcal_2, we find that when a respondent provides a reason for contraceptive discontinuation it appears in the 1st position regardless of when the respondent actually discontinued the contraceptive method. I would expect that the reason for discontinuation would be entered in the position that corresponds to the date of discontinuation from vcal_1. Is our code below used to destring vcal_2 incorrect?
DHS FORUM RESPONSE: The reason for discontinuation is recorded at the month where a contraceptive method is switched off. If there appears to be an exceptional case, please let us know its ID ( cluster #, HH# and line # ) and we will be happy to investigate it.
FOLLOW-UP QUESTION: As I note in the question above, when a respondent provides a reason for contraceptive discontinuation in the Nigeria 2013 dataset it appears in the 1st position regardless of when the respondent actually discontinued the contraceptive method. This is happening for every respondent that provides a reason for contraceptive discontinuation in the Nigeria 2013 dataset when we use the code below (examples include: Case ID: 10142, 10782, 10905, 10062, 100146...). Can you please investigate the Nigeria 2013 dataset and let us know if find the same problem?
format %67s vcal_2
gen discal1 = substr(vcal_2,1,1)
gen discal2 = substr(vcal_2,2,1)
gen discal3 = substr(vcal_2,3,1)
gen discal4 = substr(vcal_2,4,1)
gen discal5 = substr(vcal_2,5,1)
gen discal6 = substr(vcal_2,6,1)
gen discal7 = substr(vcal_2,7,1)
gen discal8 = substr(vcal_2,8,1)
gen discal9 = substr(vcal_2,9,1)
gen discal10 = substr(vcal_2,10,1)
gen discal11 = substr(vcal_2,11,1)
gen discal12 = substr(vcal_2,12,1)
gen discal13 = substr(vcal_2,13,1)
gen discal14 = substr(vcal_2,14,1)
gen discal15 = substr(vcal_2,15,1)
gen discal16 = substr(vcal_2,16,1)
gen discal17 = substr(vcal_2,17,1)
gen discal18 = substr(vcal_2,18,1)
gen discal19 = substr(vcal_2,19,1)
gen discal20 = substr(vcal_2,20,1)
gen discal21 = substr(vcal_2,21,1)
gen discal22 = substr(vcal_2,22,1)
gen discal23 = substr(vcal_2,23,1)
gen discal24 = substr(vcal_2,24,1)
gen discal25 = substr(vcal_2,25,1)
gen discal26 = substr(vcal_2,26,1)
gen discal27 = substr(vcal_2,27,1)
gen discal28 = substr(vcal_2,28,1)
gen discal29 = substr(vcal_2,29,1)
gen discal30 = substr(vcal_2,30,1)
gen discal31 = substr(vcal_2,31,1)
gen discal32 = substr(vcal_2,32,1)
gen discal33 = substr(vcal_2,33,1)
gen discal34 = substr(vcal_2,34,1)
gen discal35 = substr(vcal_2,35,1)
gen discal36 = substr(vcal_2,36,1)
gen discal37 = substr(vcal_2,37,1)
gen discal38 = substr(vcal_2,38,1)
gen discal39 = substr(vcal_2,39,1)
gen discal40 = substr(vcal_2,40,1)
gen discal41 = substr(vcal_2,41,1)
gen discal42 = substr(vcal_2,42,1)
gen discal43 = substr(vcal_2,43,1)
gen discal44 = substr(vcal_2,44,1)
gen discal45 = substr(vcal_2,45,1)
gen discal46 = substr(vcal_2,46,1)
gen discal47 = substr(vcal_2,47,1)
gen discal48 = substr(vcal_2,48,1)
gen discal49 = substr(vcal_2,49,1)
gen discal50 = substr(vcal_2,50,1)
gen discal51 = substr(vcal_2,51,1)
gen discal52 = substr(vcal_2,52,1)
gen discal53 = substr(vcal_2,53,1)
gen discal54 = substr(vcal_2,54,1)
gen discal55 = substr(vcal_2,55,1)
gen discal56 = substr(vcal_2,56,1)
gen discal57 = substr(vcal_2,57,1)
gen discal58 = substr(vcal_2,58,1)
gen discal59 = substr(vcal_2,59,1)
gen discal60 = substr(vcal_2,60,1)
gen discal61 = substr(vcal_2,61,1)
gen discal62 = substr(vcal_2,62,1)
gen discal63 = substr(vcal_2,63,1)
gen discal64 = substr(vcal_2,64,1)
gen discal65 = substr(vcal_2,65,1)
gen discal66 = substr(vcal_2,66,1)
gen discal67 = substr(vcal_2,67,1)
reshape long discal, i(caseid) j(event_time)
Thank you,
Carie
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