# Nigeria - Private farmer-Crop-2006, Third edition

Reference ID | NGA-NBS-CROP-2006-v1.0 |

Year | 2007 |

Country | Nigeria |

Producer(s) | National Bureau of Statistics (NBS) - Fedral Government of Nigeria (FGN) |

Sponsor(s) | National Bureau of Statistics - NBS - Funding Central Bank of Nigeria - CBN - Funding |

Metadata | Documentation in PDF Download DDI |

Created on | Oct 18, 2010 |

Last modified | Dec 02, 2013 |

Page views | 332157 |

Downloads | 154351 |

Sampling

Sampling Procedure

National Agricultural Sample Survey design derived from NBS 2005/07 NISH sample design. The 2005/07 NISH

sample design is a 2-stage, replicated and rotated cluster sample design with Enumeration Areas (E.As) as first stage sampling units or Primary Sampling Units (PSUs) while Housing Units constituted the second stage units (secondary sampling units).

The housing units were the Ultimate Sampling Units for the multi-subject survey.

Generally, the NISH Master Sample in each state is made up of 120 EAs drawn in 12 replicates. A replicate consists of 10 E.As. Subsets of the Master Sample are studied for modules of the NISH.

Six (6) replicates were studied for private farmers in each state and three (3) replicates for Abuja (FCT).

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.

Table 1.2 reflects the stratification procedure prior to selection within each sub-population.

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

Out of the expected 2,190 EAs, 1,963 were studied.

A total of 11, 075 holders were canvassed from 10,950 crop farming housing units because there were more than one (1) holder in some crop farming housing units

Deviations from Sample Design

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).

Response Rate

The response rate at EA level was 89.64 percent

Weighting

The variable (rf ) raising factor is computed and attached to the data file.

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.