Using Calendar Data in Single Month Format: Three Practice Exercises

As previously noted in MPC and DHS blog posts, using woman-months as a unit of analysis from IPUMS DHS simplifies analyzing contraceptive calendar data. By choosing woman-months as their unit of analysis on the IPUMS DHS website, users can make customized datasets of de-stringed and consistently coded calendar data, which saves time and minimizes errors. Researchers investigating many topics, such as length of adherence to specific contraceptive methods, timing and frequency of contraceptive failure, timing of pregnancy loss, and differences in time to conception between different populations, will find the single month format of the data useful. This format is compatible with the statistical methods commonly applied to data with a duration component.

Below are three examples of how the IPUMS DHS calendar data in single month format can be used to produce straightforward statistics relating to contraception use, in fewer steps than when using the original DHS calendar data.

EXAMPLE 1. Survival Curve of Family Planning Use.

Step 1.1. Make your customized data file.

At the IPUMS DHS website (at dhs.ipums.org), log in with your approved DHS username and password. This step is required before one can create and download a customized dataset.

Download a sample of your choice (for this example, we picked Burundi 2016), using "Woman Months" as the unit of analysis, by selecting the following variables:

CALREASON (Reason for discontinuation of contraceptive)

CALREPROD_ALLEVENTS (Numeric recode of reproductive events for woman-month)

CALCONTR (Contraception used during woman-month)

DOBCMC(Respondent's date of birth, in century months)

Other required variables, CALCMC_MONTH, CALID, and CALSEQ, are preselected for automatic inclusion in a data file with calendar data, so you do not need to add those variables yourself.

Choose Stata as the format of your data file, to fit the commands given below.

Step 1.2. Open your data file:

Either change to a working directory where your data are stored or add the full path to the command below.

cd "C:\data\IPUMS_DHS"

Open the dataset to conduct your analysis.

use "idhs_00001.dta", clear

Note: Many of the steps spelled out in the exercises in the DHS Contraceptive Calendar Tutorial can be skipped if you are using the IPUMS DHS version of calendar data.

Specifically, there is no need to destring the calendar information and to restructure it (Steps 5.1 and 5.2 of the DHS Contraceptive Calendar Tutorial exercise).

Steps 5.4 and 5.5 of the DHS Contraceptive Calendar Tutorial can also be eliminated since the calendar variables in IPUMS DHS are already in a numeric format with appropriate and consistent labels.

Our calendar sequence variable, while placing calendar moths in the correct chronological order, is not always capturing the 60 mnths immediately preceding the interview.

We therefore recommend using CALREVSEQ, which requires users to reverse the time order of the data before conducting their analyses. The commands below show you how to do that.

We are working on eliminating this step for users and will update this user note accordingly.

Step 1.3. Keep cases for the five years preceding interview and create an index variable in which months are numbered in chronological order.

Use the following command to reorder and limit cases.

bysort sample calid (calcmc_m): egen long revcalseq = rank(-calseq) keep if revcalseq <61 bysort sample calid (calcmc_m): egen long calseq_n = rank(-revcalseq)

Step 1.4. Consider the cohort of women who were all using the contraception in Month 1. Flag these cases and include all rows from those women in a sub-sample called surv_sample:

Use the following commands to make this sub-sample of contraceptive users in Month 1.

recode calcontr(0=0)(9=0)(else=1),gen(fp_use) gen fp_temp=0 replace fp_temp=1 if fp_use==1 & revcalseq==60 egen surv_sample=max(fp_temp), by(caseid)

Step 1.5. The function stset establishes the data in memory as "survival-time" data, where the variable month records time in months, the identification number for each person is provided by id(caseid), and cessation of use (i.e., failure) is marked by the first instance where fp_use==0 for each person in the sub-sample.

Use the following command to prepare these survival-time data.

stset calseq_n, id(caseid) failure(fp_use==0)

Step 1.6. The function sts list produces a table in which the column Survivor Function estimates the probability of "surviving" -- or continuously using -- some form of contraception at each month shown in the column Time.

Use the following command to create the survival-time table.

sts list if surv_sample==1

Step 1.7. A survival curve representing this table can be made easily.

Use the following command to graph the survival curve.

sts graph if surv_sample==1, by(sample)

EXAMPLE 2. Reason for method discontinuation

This example is modelled on Example 5 from the DHS Contraceptive Calendar Tutorial, modified to fit the IPUMS DHS version of calendar data. As noted on the DHS Program website, "This example [from the Contraceptive Calendar Tutorial] produces a percent distribution of the reason for discontinuation of each method discontinued in the five years preceding the survey, disaggregated by the type of method used."

Step 2.1. Use the customized dataset created for the previous example.

Step 2.2. Open your data file:

Either change to a working directory where your data are stored or add the full path to the command below.

cd "C:\data\IPUMS_DHS"

Open the dataset to conduct your analysis.

use "idhs_00001.dta", clear

Step 2.3. Keep cases relating to contraceptive discontinuation for the five years preceding interview and create an index variable to put months in chronological order.

Drop cases coded as "not in universe" and cases that occurred more than 60 months before interview.

bysort sample calid (calcmc_m): egen long revcalseq = rank(-calseq) keep if revcalseq <61 & calreason !=99

Step 2.4.Tabulate the data, using the appropriate weight.

The proper option recognizes the complex sample design using the Stata svyset command. For a single sample:

svyset idhspsu, strata(idhsstrata) weight(perweight) vce(linearized) singleunit(centered) svy: tab calreason calreprod_allevents, column per

For multiple samples, use the following command for each one:

svy: tab calreason calreprod_allevents if sample==10803, column per

Stata Output

. svyset idhspsu, strata(idhsstrata) weight[perweight] vce(linearized) singleunit(centered) svy: tab calreason calreprod_allevents, column per pweight: perweight VCE: linearized Single unit: missing Strata 1: domain SU 1: psu FPC 1: . svy: tab calreason calreprod_allevents, col per (running tabulate on estimation sample) Number of strata = 35 Number of obs = 3,737 Number of PSUs = 538 Population size = 3,990.0744 Design dfn = 503 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- reason for | discontinuation of | numeric recode of reproductive events for woman-month contraceptive | pill iud condom withdraw female c emergenc lactatio implants injectio periodic standard other mo other tr | Total ----------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------- became pregnant while | 8.303 2.708 4.504 20.48 84.85 9.185 15.39 .4543 1.453 35.17 39.13 60.03 23.29 | 5.869 ----------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------- wanted to become preg | 24.94 41.37 21.89 34.01 15.15 11.35 43.45 30.31 30.95 39.5 28.7 0 0 | 31.03 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- husband disapproved | 3.021 1.187 12.04 12.51 0 4.684 6.563 1.167 2.237 5.09 4.646 0 0 | 3.321 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- lack of access/availa | .4232 0 2.138 0 0 0 6.788 .3279 1.002 0 0 0 0 | .7265 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- cost | 0 0 .8318 0 0 0 0 .1801 0 0 0 0 0 | .0622 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- fatalistic | 1.216 2.932 0 0 0 0 0 2.346 1.22 0 0 0 0 | 1.27 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- side effects | 34.64 31.38 5.696 .3132 0 36.87 0 43.93 40.79 0 3.567 0 0 | 33.21 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- wanted more effective | 6.672 5.093 12.03 9.785 0 10.05 4.583 5.853 5.183 3.351 7.944 0 0 | 5.922 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- inconvenient to use | 4.547 3.327 9.378 6.324 0 0 0 3.236 2.413 6.46 1.087 0 20.57 | 3.502 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- infrequent sex/husban | 3.215 5.077 16.43 3.433 0 18.22 11.66 2.358 4.542 1.7 6.612 0 0 | 4.463 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- difficult to get preg | 0 1.653 .2734 0 0 0 0 .3637 .3539 0 0 0 0 | .3413 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- marital dissolution | 2.592 .5829 1.73 .275 0 0 0 .6478 1.844 0 0 0 0 | 1.381 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- other reason | 6.224 3.658 10.99 2.635 0 1.344 11.56 7.552 6.569 3.116 0 0 45.86 | 6.301 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- do not know | 4.207 1.032 2.071 10.24 0 8.302 0 1.274 1.441 5.619 8.31 39.97 10.28 | 2.607 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Total | 100 100 100 100 100 100 100 100 100 100 100 100 100 | 100 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Key: column percentage Pearson: Uncorrected chi2(156) = 1409.9456 Design-based F(60.69, 30529.27)= 9.9943 P = 0.0000

Stata Output

. bysort sample: tab calreason calreprod_allevents [iw=perweight], column nofreq --------------------------------------------------------------------------------------------------------------------------------------------------------------------------- -> sample = burundi 2016 reason for | discontinuation of | numeric recode of reproductive events for woman-month contraceptive | pill iud condom withdrawa female co emergency lactation implants/ injection periodic standard other mo | Total ----------------------+----------------------------------------------------------------------------------------------------------------------------------------------- became pregnant while | 8.30 2.71 4.50 20.48 84.85 9.18 15.39 0.45 1.45 35.17 35.17 60.03 | 5.87 ----------------------+----------------------------------------------------------------------------------------------------------------------------------------------- wanted to become preg | 24.94 41.37 21.89 34.01 15.15 11.35 43.45 30.31 30.95 39.50 28.70 0.00 | 31.03 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- husband disapproved | 3.02 1.19 12.04 12.51 0.00 4.68 6.56 1.17 2.24 5.09 4.65 0.00 | 3.32 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- lack of access/availa | 0.42 0.00 2.14 0.00 0.00 0.00 6.79 0.33 1.00 0.00 0.00 0.00 | 0.73 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- cost | 0.00 0.00 0.83 0.00 0.00 0.00 0.00 .18 0.00 0.00 0.00 0.00 | 0.06 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- fatalistic | 1.22 2.93 0.00 0.00 0.00 0.00 0.00 2.35 1.22 0.00 0.00 0.00 | 1.27 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- side effects | 34.64 31.38 5.70 0.31 0.00 36.87 0.00 43.93 40.79 0.00 3.57 0.00 | 33.21 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- wanted more effective | 6.67 5.09 12.03 9.78 0.00 10.05 4.58 5.85 5.18 3.35 7.94 0.00 | 5.92 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- inconvenient to use | 4.55 3.33 9.38 6.32 0.00 0.00 0.00 3.24 2.41 6.46 1.09 0.00 | 3.50 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- infrequent sex/husban | 3.22 5.08 16.43 3.43 0.00 18.22 11.66 2.36 4.54 1.70 6.61 0.00 | 4.46 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- difficult to get preg | 0.00 1.65 0.27 0.00 0.00 0.00 0.00 0.36 0.35 0.00 0.00 0.00 | 0.34 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- marital dissolution | 2.59 0.58 1.73 0.28 0.00 0.00 0.00 0.65 1.84 0.00 0.00 0.00 | 1.38 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- other reason | 6.22 3.66 10.99 2.63 0.00 1.34 11.56 7.55 6.57 3.12 0.00 0.00 | 6.30 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- do not know | 4.21 1.03 2.07 10.24 0.00 8.30 0.00 1.27 1.44 5.62 8.31 39.97 | 2.61 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- Total | 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 |100.00 ----------------------------------------------------------------------------------------------------------------------------------------------------------------------

EXAMPLE 3. Examine contraceptive prevalence over time.

Our third example replicates Example 6 from the DHS Contraceptive Calendar Tutorial. This exercises "calculates the proportion of women age 15-44 who were using any method of contraception in a five-year period prior to the first survey interview." Following the suggestions on the DHS Program website, the following restrictions are used: "1) limit to women age 15-44 throughout the table as the oldest woman would only be 44 years old five years before the survey, and 2) only include data for months on or before the earliest month of interview, as there may be biases for later months in which only a limited set of women provided data."

Step 3.1. Use the customized dataset created for the previous examples.

Step 3.2.Open your data file.

Either change to a working directory where the data are stored or add the full path to the 'use' command below.

cd "C:\data\IPUMS_DHS"

Open the dataset to conduct your analysis

use "idhs_00001.dta", clear

Note: As in the previous example, many of the steps spelled out in the exercise in the DHS Contraceptive Calendar Tutorial can be skipped when using the IPUMS DHS version of calendar data.

Specifically, there is no need to destring the calendar information and to restructure it (Steps 6.1 and 6.2 of the DHS Contraceptive Calendar Tutorial exercise).

The calendar variables in IPUMS DHS are already in a numeric format with appropriate and consistent labels.

Step 3.3. Keep cases relating to contraceptive discontinuation for the five years preceding the interview and create an index variable to order months chronologically.

Use the following Stata command to limit cases to 60 months before interview:

bysort sample calid (calcmc_m): egen long revcalseq = rank(-calseq) keep if revcalseq<61

Step 3.4. Calculate the women's ages in months

As we need to know the woman's age in months for every case, we will calculate a new variable, calage_m, for this purpose. We will use this variable to select women age 15-44 (more precisely, age 180-539 months, which is equal to 15 years 0 months through 44 years 11 months).

destring calcmc_month, replace generate calage_m = calcmc_month - dobcmc label variable calage_m "Age in months"

Step 3.5. Do final calculations

Notably, whereas step 6.4 of Example 6 of the DHS Contraceptive Calendar Tutorial provides instructions on calculating cmctime (century month code) and usingany (using any method), IPUMS DHS supplies ready-made variables with this content: CALCMC_MONTH and CALCONTR.

The final step is tabulating contraceptive usage by country month code, while limiting the sample to women age 15-44. The results will show the proportion of women in this age range using any contraceptive method.

For a simple tabulation of the contraceptive prevalence rate (CPR) for each month, use the following command:

tab calcmc_month calcontr if inrange(calage_m,180,539) [iw=perweight], row nofreq

Stata output:

. tab calcmc_month calcontr if inrange(calage_m,180,539) [iw=perweight], row nofreq century month | contraception used code date of | during woman-month woman-month | no contra yes,cont | Total ----------------------------------------------------- 1343 | 94.11 5.89 | 100.00 ----------------------------------------------------- 1344 | 93.45 6.55 | 100.00 ----------------------------------------------------- 1345 | 92.48 7.52 | 100.00 ----------------------------------------------------- 1346 | 91.57 8.43 | 100.00 ----------------------------------------------------- 1347 | 91.30 8.70 | 100.00 ----------------------------------------------------- 1348 | 90.99 9.01 | 100.00 ----------------------------------------------------- 1349 | 90.79 9.21 | 100.00 ----------------------------------------------------- 1350 | 90.51 9.49 | 100.00 ----------------------------------------------------- 1351 | 90.54 9.46 | 100.00 ----------------------------------------------------- 1352 | 90.31 9.69 | 100.00 ----------------------------------------------------- 1353 | 90.08 9.92 | 100.00 ----------------------------------------------------- 1354 | 89.95 10.05 | 100.00 ----------------------------------------------------- 1355 | 89.65 10.35 | 100.00 ----------------------------------------------------- 1356 | 89.46 10.54 | 100.00 ----------------------------------------------------- 1357 | 89.47 10.53 | 100.00 ----------------------------------------------------- 1358 | 89.20 10.80 | 100.00 ----------------------------------------------------- 1359 | 88.91 11.09 | 100.00 ----------------------------------------------------- 1360 | 88.83 11.17 | 100.00 ----------------------------------------------------- 1361 | 88.64 11.36 | 100.00 ----------------------------------------------------- 1362 | 88.33 11.67 | 100.00 ----------------------------------------------------- 1363 | 88.20 11.80 | 100.00 ----------------------------------------------------- 1364 | 87.95 12.05 | 100.00 ----------------------------------------------------- 1365 | 87.89 12.11 | 100.00 ----------------------------------------------------- 1366 | 87.89 12.11 | 100.00 ----------------------------------------------------- 1367 | 87.64 12.36 | 100.00 ----------------------------------------------------- 1368 | 87.50 12.50 | 100.00 ----------------------------------------------------- 1369 | 87.48 12.52 | 100.00 ----------------------------------------------------- 1370 | 87.39 12.61 | 100.00 ----------------------------------------------------- 1371 | 87.41 12.59 | 100.00 ----------------------------------------------------- 1372 | 87.47 12.53 | 100.00 ----------------------------------------------------- 1373 | 87.32 12.68 | 100.00 ----------------------------------------------------- 1374 | 87.38 12.62 | 100.00 ----------------------------------------------------- 1375 | 87.37 12.63 | 100.00 ----------------------------------------------------- 1376 | 87.32 12.68 | 100.00 ----------------------------------------------------- 1377 | 87.30 12.70 | 100.00 ----------------------------------------------------- 1378 | 87.23 12.77 | 100.00 ----------------------------------------------------- 1379 | 87.18 12.82 | 100.00 ----------------------------------------------------- 1380 | 87.17 12.83 | 100.00 ----------------------------------------------------- 1381 | 87.16 12.84 | 100.00 ----------------------------------------------------- 1382 | 87.18 12.82 | 100.00 ----------------------------------------------------- 1383 | 87.05 12.95 | 100.00 ----------------------------------------------------- 1384 | 86.97 13.03 | 100.00 ----------------------------------------------------- 1385 | 87.02 12.98 | 100.00 ----------------------------------------------------- 1386 | 87.00 13.00 | 100.00 ----------------------------------------------------- 1387 | 86.89 13.11 | 100.00 ----------------------------------------------------- 1388 | 86.74 13.26 | 100.00 ----------------------------------------------------- 1389 | 86.61 13.39 | 100.00 ----------------------------------------------------- 1390 | 86.48 13.52 | 100.00 ----------------------------------------------------- 1391 | 86.33 13.67 | 100.00 ----------------------------------------------------- 1392 | 86.02 13.98 | 100.00 ----------------------------------------------------- 1393 | 85.76 14.24 | 100.00 ----------------------------------------------------- 1394 | 85.42 14.58 | 100.00 ----------------------------------------------------- 1395 | 85.21 14.79 | 100.00 ----------------------------------------------------- 1396 | 85.10 14.90 | 100.00 ----------------------------------------------------- 1397 | 84.60 15.40 | 100.00 ----------------------------------------------------- 1398 | 84.24 15.76 | 100.00 ----------------------------------------------------- 1399 | 83.79 16.21 | 100.00 ----------------------------------------------------- 1400 | 83.26 16.74 | 100.00 ----------------------------------------------------- 1401 | 82.88 17.12 | 100.00 ----------------------------------------------------- 1402 | 82.51 17.49 | 100.00 ----------------------------------------------------- 1403 | 82.29 17.71 | 100.00 ----------------------------------------------------- 1404 | 81.84 18.16 | 100.00 ----------------------------------------------------- 1405 | 80.79 19.21 | 100.00 ----------------------------------------------------- 1406 | 79.77 20.23 | 100.00 ----------------------------------------------------- 1407 | 84.50 15.50 | 100.00 ----------------------------------------------------- Total | 87.27 12.73 | 100.00

To produce properly weighted results using the svy parameters

svyset psu [pweight=perweight], strata(domain)

Tabulate CPR for women 15-44 - including standards error and 95% Confidence interval

svy, subpop(if inrange(calage_m,180,539)): mean calcontr, over(calcmc_month) nolegend

Stata output:

. * Tabulate CPR for women 15-44 including standards error and 95% Confidence interval . svy, subpop(if inrange(calage_m,180,539)): mean calcontr, over(calcmc_month) nolegend (running mean on estimation sample) Survey: Mean estimation Number of strata = 35 Number of obs = 1,036,140 Number of PSUs = 554 Population size = 1,036,140 Subpop. no. obs = 877,616 Subpop. size = 881,339.26 Design df = 519 -------------------------------------------------------------------------- | Linearized | Mean Std. Err. [95% Conf. Interval] -------------------------------------------------------------------------- c.calcontr@calcmc_month | -------------------------------------------------------------------------- 1343 | .0588519 .0070553 .0449914 .0727124 -------------------------------------------------------------------------- 1344 | .0655279 .0042953 .0570896 .0739661 -------------------------------------------------------------------------- 1345 | .0752112 .003641 .0680583 .0823641 -------------------------------------------------------------------------- 1346 | .0843261 .0035598 .0773326 .0913195 -------------------------------------------------------------------------- 1347 | .0870258 .0032516 .0806379 .0934138 -------------------------------------------------------------------------- 1348 | .090141 .0033264 .0836061 .0966759 -------------------------------------------------------------------------- 1349 | .0920578 .0034223 .0853345 .0987811 -------------------------------------------------------------------------- 1350 | .0948838 .0035162 .0879762 .1017915 -------------------------------------------------------------------------- 1351 | .0946134 .0034487 .0878382 .1013885 -------------------------------------------------------------------------- 1352 | .0968852 .0034907 .0900276 .1037429 -------------------------------------------------------------------------- 1353 | .0991992 .0034889 .092345 .1060533 -------------------------------------------------------------------------- 1354 | .1005312 .0034592 .0937354 .107327 -------------------------------------------------------------------------- 1355 | .1034984 .0035279 .0965677 .1104291 -------------------------------------------------------------------------- 1356 | .1053634 .0034672 .0985519 .1121748 -------------------------------------------------------------------------- 1357 | .1052634 .0034966 .0983942 .1121326 -------------------------------------------------------------------------- 1358 | .1080461 .0035111 .1011483 .1149439 -------------------------------------------------------------------------- 1359 | .1108987 .0035466 .1039312 .1178662 -------------------------------------------------------------------------- 1360 | .1117398 .0035403 .1047848 .1186949 -------------------------------------------------------------------------- 1361 | .1135538 .0035699 .1065405 .1205671 -------------------------------------------------------------------------- 1362 | .1166647 .0036128 .1095673 .1237622 -------------------------------------------------------------------------- 1363 | .1180429 .0036953 .1107832 .1253025 -------------------------------------------------------------------------- 1364 | .1204509 .0037612 .1130618 .1278399 -------------------------------------------------------------------------- 1365 | .1211401 .0036802 .1139102 .1283701 -------------------------------------------------------------------------- 1366 | .1211401 .0036839 .1139028 .1283773 -------------------------------------------------------------------------- 1367 | .1235914 .0037691 .1161869 .1309959 -------------------------------------------------------------------------- 1368 | .1249733 .0038894 .1173323 .1326143 -------------------------------------------------------------------------- 1369 | .1251814 .0039804 .1173617 .1330012 -------------------------------------------------------------------------- 1370 | .1261237 .0040045 .1182567 .1339907 -------------------------------------------------------------------------- 1371 | .1258944 .0039272 .1181793 .1336095 -------------------------------------------------------------------------- 1372 | .125331 .0039111 .1176474 .1330146 -------------------------------------------------------------------------- 1373 | .1267679 .0039344 .1190386 .1344971 -------------------------------------------------------------------------- 1374 | .1261537 .0039048 .1184825 .1338249 -------------------------------------------------------------------------- 1375 | .1263183 .0038492 .1187564 .1338803 -------------------------------------------------------------------------- 1376 | .1267982 .0037484 .1194342 .1341622 -------------------------------------------------------------------------- 1377 | .1269583 .0038316 .119431 .1344856 -------------------------------------------------------------------------- 1378 | .1277215 .0037492 .120356 .1350871 -------------------------------------------------------------------------- 1379 | .1282363 .0037596 .1208504 .1356221 -------------------------------------------------------------------------- 1380 | .1282779 .0038033 .1208061 .1357497 -------------------------------------------------------------------------- 1381 | .1284324 .0038046 .1209581 .1359066 -------------------------------------------------------------------------- 1382 | .1281511 .0038044 .1206773 .135625 -------------------------------------------------------------------------- 1383 | .1295071 .0037112 .1222162 .136798 -------------------------------------------------------------------------- 1384 | .1302675 .0036768 .1230443 .1374907 -------------------------------------------------------------------------- 1385 | .1298032 .0036498 .122633 .1369734 -------------------------------------------------------------------------- 1386 | .1300379 .0036107 .1229445 .1371314 -------------------------------------------------------------------------- 1387 | .1311499 .0036866 .1239074 .1383924 -------------------------------------------------------------------------- 1388 | .1326131 .0037316 .1252821 .1399441 -------------------------------------------------------------------------- 1389 | .1339158 .003779 .1264918 .1413398 -------------------------------------------------------------------------- 1390 | .135236 .0038456 .1276811 .1427908 -------------------------------------------------------------------------- 1391 | .1366614 .0038396 .1291183 .1442046 -------------------------------------------------------------------------- 1392 | .1398269 .0039895 .1319892 .1476645 -------------------------------------------------------------------------- 1393 | .1423745 .0039897 .1345366 .1502124 -------------------------------------------------------------------------- 1394 | .1457545 .0040103 .1378761 .1536329 -------------------------------------------------------------------------- 1395 | .1479303 .0039927 .1400865 .1557741 -------------------------------------------------------------------------- 1396 | .1490465 .0040047 .1411791 .1569139 -------------------------------------------------------------------------- 1397 | .1540173 .0041676 .1458298 .1622048 -------------------------------------------------------------------------- 1398 | .157558 .0042652 .1491789 .1659371 -------------------------------------------------------------------------- 1399 | .162141 .0042749 .1537427 .1705392 -------------------------------------------------------------------------- 1400 | .1673764 .0043297 .1588705 .1758823 -------------------------------------------------------------------------- 1401 | .1712234 .0043755 .1626275 .1798192 -------------------------------------------------------------------------- 1402 | .1749233 .0044151 .1662496 .1835971 -------------------------------------------------------------------------- 1403 | .1770666 .0048485 .1675416 .1865917 -------------------------------------------------------------------------- 1404 | .1816224 .0060429 .1697509 .1934939 -------------------------------------------------------------------------- 1405 | .1920651 .0079036 .1765382 .207592 -------------------------------------------------------------------------- 1406 | .2023279 .0126524 .1774717 .2271841 -------------------------------------------------------------------------- 1407 | .1549731 .0257704 .104346 .2056002 --------------------------------------------------------------------------

Note: CMC 1333 is January 2011, CMC 1345 is January 2012, CMC 1357 is January 2013, CMC 1369 is January 2014, CMC 1381 is January 2015. Thus CMC 1327 is July 2010 and CMC 1386 is June 2015. For discussion of how century months are calculated and interpreted, see the variable description for DOBCMC.

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Using Calendar Data in Single Month Format: Three Practice Exercises

EXAMPLE 1. Survival Curve of Family Planning Use.

Step 1.1. Make your customized data file.

Step 1.2. Open your data file:

Step 1.3. Keep cases for the five years preceding interview and create an index variable in which months are numbered in chronological order.

Step 1.4. Consider the cohort of women who were all using the contraception in Month 1. Flag these cases and include all rows from those women in a sub-sample called surv_sample:

Step 1.6. The function sts list produces a table in which the column Survivor Function estimates the probability of "surviving" -- or continuously using -- some form of contraception at each month shown in the column Time.

Step 1.7. A survival curve representing this table can be made easily.

EXAMPLE 2. Reason for method discontinuation

Step 2.1. Use the customized dataset created for the previous example.

Step 2.2. Open your data file:

Step 2.3. Keep cases relating to contraceptive discontinuation for the five years preceding interview and create an index variable to put months in chronological order.

Step 2.4.Tabulate the data, using the appropriate weight.

Stata Output

Stata Output

EXAMPLE 3. Examine contraceptive prevalence over time.

Step 3.1. Use the customized dataset created for the previous examples.

Step 3.2.Open your data file.

Step 3.3. Keep cases relating to contraceptive discontinuation for the five years preceding the interview and create an index variable to order months chronologically.

Step 3.4. Calculate the women's ages in months

Step 3.5. Do final calculations

Stata output:

Stata output:

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