After each successive wave of contacts with a particular group of potential respondents, the researcher should run a sensitivity analysis That is, one should ascertain how different the non-respondents would have to be from the respondents in order to alter the decision one would make based on the data supplied by the current respondents.
if the most extreme foreseeable answers by the non-respondents would not alter the decision, no further efforts are required.
Subjective Estimates
When it is no longer practical to increase the response rate, the researcher can estimate subjectively,, the nature and effect of the non-respondents.
That is, the researcher, based on experience and the nature of the survey makes a subjective research evaluation of the probable effects of the non-response error.
For example, the fact that those most interested in a product are most likely to I return a mail questionnaire gives the researcher some confidence that non-respondents are less interested in the topic than respondents.
Imputation Estimates
Imputation estimates involve imputing attributes to the non-respondents based on the characteristics of the respondents.
These techniques can be used missing Respondents or for item non-response. For example, a respondent who fails to report income may be "assigned" the income of a respondent with Similar demographic characteristic.
A number of other imputation approaches to item non-response exist.
A common approach to differential non-response by groups defined by age, race, social class, and so forth is to weigh the responses of those who reply in a manner that offsets the non-response rate.
This, of course, assumes that the non-respondents in each group and that the percentage of the population belonging to each group is known.
Trend Analysis
Trend analysis is similar to the imputation technique, except that the attributes of the non-respondents are assumed to be similar to a projection of the trend shown between early and late respondents.
However, trend analysis should only be used when there are logical reasons to believe the trend will extend to the non-respondents.
Measurement using Sub samples
Sub-sampling of non-respondents, particularly when a mail survey was the original been found effective in reducing non-response error.
Concentrated attention on a sub-sample of non-respondents, generally using telephone or personal interviews, can often yield a high response rate within the sub-sample.
using standard statistical procedures, the values obtained in the sub-sample can be projected to the entire group of non-respondents and the overall survey results adjusted to take into account the non-respondents.
The primary drawback to this technique is the cost involved.
After each successive wave of contacts with a particular group of potential respondents, the researcher should run a sensitivity analysis That is, one should ascertain how different the non-respondents would have to be from the respondents in order to alter the decision one would make based on the data supplied by the current respondents.
if the most extreme foreseeable answers by the non-respondents would not alter the decision, no further efforts are required.
Subjective Estimates
When it is no longer practical to increase the response rate, the researcher can estimate subjectively,, the nature and effect of the non-respondents.
That is, the researcher, based on experience and the nature of the survey makes a subjective research evaluation of the probable effects of the non-response error.
For example, the fact that those most interested in a product are most likely to I return a mail questionnaire gives the researcher some confidence that non-respondents are less interested in the topic than respondents.
Imputation Estimates
Imputation estimates involve imputing attributes to the non-respondents based on the characteristics of the respondents.
These techniques can be used missing Respondents or for item non-response. For example, a respondent who fails to report income may be "assigned" the income of a respondent with Similar demographic characteristic.
A number of other imputation approaches to item non-response exist.
A common approach to differential non-response by groups defined by age, race, social class, and so forth is to weigh the responses of those who reply in a manner that offsets the non-response rate.
This, of course, assumes that the non-respondents in each group and that the percentage of the population belonging to each group is known.
Trend Analysis
Trend analysis is similar to the imputation technique, except that the attributes of the non-respondents are assumed to be similar to a projection of the trend shown between early and late respondents.
However, trend analysis should only be used when there are logical reasons to believe the trend will extend to the non-respondents.
Measurement using Sub samples
Sub-sampling of non-respondents, particularly when a mail survey was the original been found effective in reducing non-response error.
Concentrated attention on a sub-sample of non-respondents, generally using telephone or personal interviews, can often yield a high response rate within the sub-sample.
using standard statistical procedures, the values obtained in the sub-sample can be projected to the entire group of non-respondents and the overall survey results adjusted to take into account the non-respondents.
The primary drawback to this technique is the cost involved.
