Stratification Variable: Variable or variables by which a study population is divided up into strata (or groups) in order to select a stratified sample.

Disproportionate Stratified Sample: Stratified sample where the number of Foodservice Operators selected from each strata is not proportional to the number of units in each strata in the population. Disproportionate Stratified Sampling implies that raising factors, or “sampling weights”, need to be used to obtain national estimates from the sample.

Stratified Samples can reduce sampling error.

These studies ensure particular groups within the population are adequately represented in the sample.

They are highly accurate when conducted properly.

A panel permits correlating change in the outcomes with change in other factors.

A panel approach may reduce the effort of the second and subsequent rounds making it more economical.

A panel can more accurately measure change within the panel.

Using panel research reduces the fielding costs and reflects the behavior of the panel members.

Panels are harder to manage and entail long-term commitments between data users and producers.

Panels are subject to attrition (respondent fatigue, migration, disappearance from market, etc.).

A panel is more vulnerable to bias from incentives.

Panels are inherently less accurate in representing the industry.