280 likes | 620 Views
Introduction to Sampling : Censuses vs. Sample Surveys. Module 3 Session 4. Session Objectives. Distinguish between censuses and sample surveys Demonstrate the linkages between censuses and surveys Discuss the challenges of conducting censuses and large scale surveys in Uganda
E N D
Introduction to Sampling: Censuses vs. Sample Surveys Module 3 Session 4
Session Objectives • Distinguish between censuses and sample surveys • Demonstrate the linkages between censuses and surveys • Discuss the challenges of conducting censuses and large scale surveys in Uganda • Distinguish between random and non random samples • Identify the types and/or sources of errors in censuses and surveys • Discuss how errors can be minimised in censuses and surveys
Reminder of Definitions • Population: totality of all units of interest • Sample: part/subset of the population • Censuses: inquiries that cover the whole population eg. Uganda Population and Housing Census, CIS, EMIS, HMIS, LOGICS, etc • Sample surveys are inquiries that cover part/subset of the population eg. UDHS, UNHS, NSDS, etc • Sampling Frame: list of distinct and distinguishable units in the population of interest; beginning step in almost all random sampling schemes, e.g. numbers written on households before the census night
Other Definitions • Defacto census- covers all persons found within the borders of a particular territory/country at a particular point in time-census night • Dejure census-tallies people according to their regular or legal residence
Sampling Frames • Sources • Administrative records-eg • Hospital records • Birth and Death Registers • LC lists • Voters’ register • School registers • etc • Construct your own
Disadvantages of various sources of sampling frames • Administrative records may not be up to date • Constructing your own may be too costly especially in large scale surveys
Provide benchmark data for monitoring, planning and policy formulation eg we need data for UPE monitoring, poverty monitoring Election monitoring Resource allocation Role of censuses in Uganda
Provide small area statistics - basic data disaggregated to the lowest administrative unit e.g we use census data to know the number of people in each village, sub county and district for planning purposes Show the actual status of the various indicators Health indicators-mortality, disease prevalence Fertility trends, population growth rate Role of censuses in Uganda (cont.)
Linkages between censuses and sample surveys • Sample surveys can be used as a substitute for censuses • Sample surveys can be used to supplement census data • Sample surveys can be used to pretest census materials, procedures and methods • Censuses are used as a basis for surveys conducted between censuses • Sample surveys can be used to monitor census results
Challenges of Conducting Censuses and Large Scale Sample Surveys • Challenges of Surveys and Censuses Mubiru James.ppt
Types of Samples • There two types of samples: • Random and Non random samples • Random samples are those whose composition is not influenced by the sampler • Non Random samples are those whose composition is influenced by the sampler
Advantages of Random Samples • Objective and hence inferences based on them are reliable
Disadvantages of Random Samples • Costly to select • Need skilled manpower to get a random sample • For some surveys, random sampling may not be the best because the sample may not provide the required data.
Advantages of Non Random Samples • Easy and cheap to select since selection and substitution can be done at will • Since they are done at will, the data needed can be easily obtained
Disadvantages of Non Random Samples • Subjective and hence inferences based on them are biased • Sampling errors can not be estimated
Types of Errors • There are two types of errors, namely: • Sampling errors • Non sampling errors
Sampling Errors/Biases • Sampling errors are absent in censuses • Their causes include: • Use of defective sampling frame • Use of defective sampling procedures • Use of an estimation method that does not correspond to the sampling design
Non Sampling Errors • Non sampling errors occur both in censuses and sample surveys but are more pronounced in censuses
Sources of Non sampling Errors • Defective sampling frames resulting into coverage errors • Under coverage • Over coverage • Conceptual problems • Physical environment • Inadequacy of enumerators and supervisors
Sources continued • Language problems – translation • Problems of measurement • Response problems • Non response problems • Poor cartographic work • Poorly designed questionnaires/instruments • Poorly trained enumerators/supervisors • Unqualified enumerators/supervisors
How Errors can be Minimised • Supervision • Training • Use of the appropriate estimation method • Publicity of the survey • Testing the survey instruments
Sampling in the Research Process • Problem • Objectives • Hypotheses • Methodology • Data Sources • Target population • Census or sample? • If sample? • What is the sampling design?