Nigeria - SOCIO ECONOMIC SURVEY, CROP-2005 (PRIVATE FARMERS), Second round

National Agricultural Sample Survey (Private Farmers Questionnaire Survey) samples were derived from the National Bureau of Statistics 2000/05 NISH sample design. The NISH employed a 2-stage, replicated and rotated cluster sample design with enumeration areas (EAs) as first stage sampling units [Primary Sampling Units (PSU)], while the housing units constituted the second stage sampling units [Secondary Sampling Units]. The housing units were the ultimate sampling units for the multi-subject survey.

The Private Farmers' Survey total sample size was 10,950 Farming Housing Units. In each State, the housing units were stratified into Farming and Non-Farming. Five housing units were systematically selected in each Enumeration Area. A sample size of 300 farming housing units was drawn from each State and 150 from FCT, Abuja. The total sample size of 10,950 could provide estimates at national and State levels.

For the NASS (Private Farmers), 5 farming housing Unit (FHUs) were selected systematically after stratifying the housing units into farming and non-farming housing units where all the holders within the selected farming housing units were interviewed using the private farmers questionnaires.

Estimation Procedures:
Let the probability of selecting the EA be fj and the probability of selecting the housing unit be fk. Then the product f = fjfk = 1 where fj = n and fk = h
Wj k N H.

For NASS (Private Farmers)
^ n h
Ys = N S FH S x s j k
n j=1 m k=1

n m
= N FH S S xs j k
n h j=1 k=1

n h
= Ws j k S S x s j k
j=1 k=1

^
Where Ys is the state Estimate

N = Total number of EAs in the 5th State
n = Selected number of EAs in 5th State
FH = Total number of farming housing units listed.
M = Selected number of farming housing units
Xsjk is the value of the element of farming housing unit (FHUs) in the kth housing unit of jth EA in the 8th State.
Ws j k is the weight.


. National Estimate:
^ 37 ^
YN = S Ys
s=1

^ ^
Where YN is the National Estimate and Ys is the state Estimate.

Variance Estimate (Jackknife Method)

To estimate variances using the Jackknife method will require forming replicate from the full sample by randomly eliminating one sample cluster [Enumeration Area (EA] at a time from a state containing k EAs, k replicated estimates are formed by eliminating one of these, at a time, and increasing the weight of the remaining (k-1) EAs by a factor of k/(k=1). This process is repeated for each EA.

For a given state or reporting domain, the estimate of the variance of a rate, r, is given by
k
Var(r ) = (Se)2 = 1 S (ri - r)2 where (Se) is the standard error, k is
K(k-1) i=1

The number of EAs in the state of reporting domain.

r is the weighted estimate calculated from the entire sample of EAs in the state or reporting domain.
ri is equal to kr = (k-1) r(i) , where

r(i) is the re-weight estimate calculated from the reduced sample of k-1 EAs.

To obtain an estimate of the variance at a higher level, say, at the national level, the process is repeated over all states, with k redefined to refer to the total number of EAs (as opposed to the number in the states).