Sampling Techniques. Data from a multi-country study comparing coverage survey sampling methods was used for this study. Coverage surveys were conducted from 2014-2015 in three lymphatic filariasis (LF) endemic districts in Burkina Faso, three LF endemic districts in Malawi and one LF endemic district in Uganda. One sampling method was used per district in Burkina Faso and Malawi, and all three sampling methods were used in one district in Uganda. The three sampling method techniques that were used, are specified below.
Sampling Techniques third edition, New York: Xxxx Xxxxx & Sons, Inc., 1977) Westat used FEHLPS to estimate the standard deviation of homeowner estimated rents for each COLA area and the Washington, DC area. Westat also used the results of the survey to estimate the standard deviation of market rents by area, except for the Caribbean and DC areas. For these areas, Westat used the results of the 2002 COLA survey because that survey had more observations and covered the general population, not just Federal employees. From the surveys, Westat developed sample sizes for owner and renters for the COLA areas and the Washington, DC area. Westat developed two sets each for owners and renters. One set was the sample size necessary for estimating rent or rental equivalence within a margin of error of +/¥ $500 in annual rent with 90 percent confidence level, and the other was the sample size for estimating rent or rental equivalence at the same margin of error at the 95 percent confidence level. Subsequent to the 2003 Alaska COLA survey, OPM modified the renter sample sizes for the Alaska and DC areas based on the additional rental data that OPM had collected in these areas. Appendix B shows the sample sizes Westat recommended, as modified by OPM. Within each area, OPM limited the geographic scope of GPRES to the zip code areas in which OPM collected rental data in the annual COLA surveys. In the Washington, DC area, OPM further allocated the sample among the District of Columbia and the Counties of Xxxxxxxxxx, MD; Prince Xxxxxxx, MD; Arlington, VA; Fairfax, VA; and Prince Xxxxxxx, VA; and the independent cities therein, based on the relative numbers of owners and renters within these areas as reflected by the 2000 Census. OPM obtained approval for GPRES from the Office of Management and Budget (OMB) as required by 5 CFR Part 1320, and OMB assigned GPRES an information collection number. Federal surveys and other information collections that Federal agencies conduct are covered by the Paperwork Reduction Act (44 U.S.C. 3501 et seq.). Participation in GPRES was voluntary, and any identifying information regarding the respondents is protected under the Privacy Act (5 U.S.C. 552a) and the Freedom of Information Act (5 U.S.C. 552).
Sampling Techniques. In each community, 25 respondents (10 Ife household heads and 15 Modakeke household heads) were randomly selected for interview via questionnaire guides. The reason is that the number of tenants in each of the villages is usually more than double that of the landowners. In all, a total of 100 respondents were interviewed. To gather relevant information, other people interviewed include village heads/chiefs, landowners living in the villages, absentee landowners and tenants. Before the commencement of the study, visits were made to the Aafin of the Ooni of Ife and the Aafin Ogunsua of Modakeke, compound heads (Baale and Bale) of notable compounds that own villages where tenants are accommodated, and periodic meetings of the selected farming communities to gather relevant information regarding the operation of tenancy agreement after the settlement of past land conflicts. The data collected were analyzed through the use of descriptive statistics and inferential statistics such as t-test of significance between two means. RESULTS AND DISCUSSIONS Socioeconomic Characteristics of the Respondents Socioeconomic characteristics are important attributes of farmers. They help to shape the entrepreneurial abilities of farmers in rational decision making, particularly those relating to agricultural enterprises [6]. Results in Table 1 show that the respondents were predominantly male (90% landowners and 92% tenants). This is usually the picture of most agricultural communities in Africa. However, the very few female tenants in the study area reported that they hired laborers to work on their farm plots. The majority (79.6%) of the landowners were above age 60 years while the majority (72.6%) of the tenants were in between the age bracket (41- 60). These age distributions imply that most of the landowners were relatively old while most of the tenants were relatively young and in their active years. Most of the tenant farmers are the second generation of the original migrants. This was also the observation of [9].
