Nigeria - Private farmer-Livestock-Poultry-2006, Third edition

Total sample sizes of 32,850 Farming Housing Units (FHUs) were drawn from 2,190 EAs. In each state, 900 FHUs drawn from 60 EAs were studied. Four hundred and fifty (450) FHUs from 30 EAs were studied in (FCT), Abuja. The listings of housing units in the selected EAs were updated before they were stratified into farming and non-farming housing units. The farming housing units were further stratified into Crop Farming Housing Units (CFHU), Livestock Farming Housing Units (LFHU) and Fishing Farming Housing Units (FFHUs). In each EA, 5 FHUs were studied for crop farming, 5 FHUs were covered for livestock and 5 FHUs for fishery. At each level of selection, housing units were systematically selected using different random start.

All households in the HUs that qualified as farming households were served with relevant private farmers questionnaires.

Out of 2,190 EAs to be covered, 2010 Livestock/Poultry EAs were actually studied. So also out of 10,950 Livestock/Poultry Holders expected to be to be covered, 4,961 Livestock/Poultry Holders were actually studied


Variance Estimate (Jackknife Method)
Estimating 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
k(k-1) i=1

where (Se) is the standard error,
k is the number of EAs in the state or reporting domain.

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

r(i) is the re-weighted 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).


At Enumeration Area (EA) level the response rate was 91.78 per cent while at Livestock/Poultry holder level, the response rate was 45.31 per cent


The formula adopted in calculating the design weights for the survey data (sample results) were as follows:

(i) The probability of selecting an EA within a state was obtained by dividing the total number of EAs sampled in a
state by total number of EAs in that particular state. Let this be represented by fj. That is,
fj = (Total Number of EAs sampled in a state)/(Total Number of EAs in that particular State)

(ii) Likewise, the probability of selecting an housing unit (HU) within an EA was obtained by dividing the total number
of housing units selected in an EA by the total number of housing units (HUs) listed in that particular EA. Let this be
represented by fk. That is,
fk = (Total Number of HUs selected in an EA)/(Total Number of HUs listed in that particular EA)

Then the product (fj) x (fk) represented by f is the sampling fraction for each of the corresponding study unit (Enumeration Area) for all the 1,920EAs canvassed throughout the 36 states of the Federation and FCT, Abuja. The inverse of the sampling fraction is known as the design weight and was applied accordingly to all the study units.

Mathematically,
Design weight = ((Total number of EAs in a state)/(Total number of EAs sampled in that particular state)) X ((Total Number of HUs listed in an EA)/(Total Number of HUs selected in that particular EA))

The above value was obtained for each of the 2,190EAs canvassed throughout the 36 states of the Federation and FCT, Abuja. Thereafter, adjustment factors were applied to adjust for the non-responses.