Survey frame and sample selection

The target population for the July 31 crop production estimates includes all farms in Canada enumerated in the Census of Agriculture with the exception of institutional farms, farms on Indian reserves and farms from the Northwest Territories, Yukon and Atlantic region.

Every five years, the Census of Agriculture collects information on agricultural operations across Canada, including institutional farms, community pastures, Indian reserves, etc. The Census of Agriculture provides a list of farms and their crop areas from which probability sample for the July 31 crop production estimates is selected.

Probability surveys can use two types of sampling frames, list and area. In the July 31 Crop Production Survey, only the list frame is used in sample selection. This list frame is stratified into homogenous groups on the basis of Census characteristics (such as farm size and crop area) and sub-provincial geographic boundaries. A sample of approximately 15,100 farms was drawn from the list frame for the July 31 Crop Production Survey.

Data collection

Data collection for the July 31 Crop Production Survey was carried out from July 25 to August 4, 2008.

Data collection for field crop surveys is undertaken using Computer assisted telephone interview (CATI).

Edit and imputation

With the introduction of the CATI system, it is now possible to implement edit procedures at the time of the interview. Computer programmed edit checks in the CATI system inform interviewers during the interview of possible data errors, which can then be corrected immediately by the interviewer and respondent. CATI significantly reduces the need for subsequent telephone follow-up, thereby reducing respondent burden and survey processing time.

Response rate

Usually by the end of the collection period, 80% of the questionnaires have been fully completed. The refusal rate to the survey is approximately 6 to 7%. The remainder of the sample unaccounted for, can be explained by non-contact. Initial sample weights are adjusted (a process called raising factor adjustment) in cases of total and partial non-response.

Sampling and non-sampling errors

The statistics contained in this publication are based on a random sample of agricultural operations and, as such, are subject to sampling and non-sampling errors. The overall quality of the estimates depends on the combined effect of these two types of errors.

Sampling errors arise because estimates are derived from sample data and not the entire population. These errors depend on factors such as sample size, sampling design and the method of estimation. An important feature of probability sampling is that sampling errors can be measured from the sample itself.

Non-sampling errors are errors which are not related to sampling and may occur throughout the survey operation for many reasons. For example, non-response is an important source of non-sampling error. Coverage, differences in the interpretation of questions, incorrect information from respondents, mistakes in recording, coding and processing of data are other examples of non-sampling errors.

Estimation

The survey data collected are weighted in order to produce unbiased level indicators which are representative of the population. These level indicators then undergo a validation process, based on subject matter analysis and consultation with provincial statisticians, before a final estimate is published.

Revisions

The crop production estimates contained in this publication reflect producers’ production expectations as of July 31. Producers’ production expectations will be surveyed again in September as harvest progresses. Production will be estimated after the harvest in November.

Data quality

The July 31 crop production estimates are based on level indicators obtained from a probability survey of farming operations. The potential error introduced by sampling can be estimated from the sample itself by using a statistical measure called the coefficient of variation (c.v.). Over repeated surveys, 95 times out of 100, the relative difference between a sample estimate and what should have been obtained from an enumeration of all farming operations would be less than twice the coefficient of variation. This range of values is referred to as the confidence interval. While published estimates may not exactly equal the level indicators (due to the validation and consultation process), these estimates do remain within the confidence interval of the survey level indicators. For the July 31 Crop Production Survey, c.v.’s at the Canada level range from 1% to 10% for the major crops.

Data confidentiality

Data confidentiality is ensured under the Statistics Act, which prohibits the divulging of individual or aggregated data where individuals or businesses might be identified.