# Tanzania - Demographic and Health Survey 1991-1992, Tanzania

Reference ID | tza-bos-dhs-1991-v1 |

Year | 1991 - 1992 |

Country | Tanzania |

Producer(s) | Tanzania. Bureau of Statistics - Planning Commission |

Sponsor(s) | United States Agency for Intemational Development - USAID - Funding |

Collection(s) |

Created on | May 22, 2013 |

Last modified | Nov 14, 2016 |

Page views | 4805 |

Downloads | 0 |

Data Appraisal

Estimates of Sampling Error The results from sample surveys are affected by two types of errors, non-sampling error and sampling error. Non-sampling error is due to mistakes made in carrying out field activities, such as failure to locate and interview the correct household, errors in the way the questions are asked, misunderstanding on the part of either the interviewer or the respondent, and data entry errors. Although efforts were made to minimize this type of error during the design and implementation of the TDHS, non-sampling errors are impossible to avoid and difficult to evaluate statistically. Sampling errors, on the other hand, can be measured statistically. The sample of women selected in the TDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each one would have yielded results that differed somewhat from the actual sample selected. The sampling error is a measure of the variability between all possible samples; although it is not known exactly, it can be estimated from the survey results. Sampling error is usually measured in terms of standard error of a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which one can be reasonably assured that, apart from non-sampling errors, the true value of the variable for the whole population falls. For example, for any given statistic calculated from a sample survey, the value of that same statistic as measured in 95 percent of all possible samples with the same design (and expected size) will fall within a range of plus or minus two times the standard error of that statistic. If the sample of women had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the Tanzania DHS sample designs depended on stratification, stages, and clusters. Consequently, it was necessary to utilize more complex formulas. The computer package CLUSTERS, developed by the International Statistical Institute for the World Fertility Survey, was used to assist in computing the sampling errors with the proper statistical methodology. Note: See detailed sampling error calculation in the APPENDIX C of the final 1991-1992 Tanzania Demographic and Health Survey report. | |

Data Quality Notes The following Data Quality Tables are provided in the Final Report: - Household age distribution - Age distribution of eligible and interviewed women - Completeness of reporting - Birth by calendar year since birth - Reporting of age at death in days - Reporting of age at death in months |