which sampling method does not require a frame
Many sampling methods are used in sampling where there is a frame, like with clusters or stratified sampling. But one method does not require a frame, and that is systematic random sampling. Another method that does not require a frame would be total survey design.
Systematic random sampling is a randomized sampling method that makes it possible to have a sample that is not biased. The idea is to have every case in the population of interest have an equal chance of being selected, which is why it is called “systematic”. The only way this can be done with just one random number is if the population size and the sample size are both integers together that have no common divisors other than 1. Systematic random sampling can be used in areas without frames to better select a sample.
when is a frame necessary
A frame is necessary when we need a list of elements (units) from which the sample is selected. The frame should have information about the characteristics or attributes that can be used to make the selection of a sample from the frame. Without a frame, it is impossible to select a systematic sample from the population. Frame is an essential element in sampling design where there is need for probability sampling methods.
The frame is the universe from which the sample is selected. The universe is a list of objects, people or units and can either be complete or incomplete.
When a frame does not exist, list all items (e.g., towns, schools), which are then removed from the master list for selection of a sample as in Figure 1 where K = universe.
or in case of population with characteristics that cannot be interpreted easily or directly (e.g., education attainment) (Figure 2). (See the section “Selection of a sample from a population” in the article on sampling.)
types of frames
There are different types of sampling frames. One is the list frame and the other is the structure frame. The list frame is composed of complete and updated information on every unit in a target population. List frames are usually prepared for conducting census operations. Structure frames, on the other hand, contain some incomplete or missing information about some units in the population, making them less desirable in surveys. Complete updating of the structure is not possible (Duncan 1994). Examples of a structure frame include the telephone directory and lists of registered voters.
The list frame is composed of complete and updated information on every unit in a target population. Lists, as defined by Dunn and Kolsti (1986), are collections of individuals that represent a specific population. The main difference between a list and a sample is that the list usually contains all the members of the population, whereas the sample usually does not contain all of the members in the population. A list consists of one or more complete units (e.g., neighborhoods, ZIP codes or households) that depict every individual who lives there. Lists often fail to reflect the population because they are not updated and may include incomplete units. Incomplete units in a list may be intentional or due to error.
The structure frame is composed of incomplete and updated information about some individuals or units in the population. Structure frames are quite useful for conducting surveys. As such, they are often used as samples for social science research, but there are certain drawbacks with this method (Kimmerle 1988; Dunn 1994). For example, data from the structure frame may be incomplete (e.g. registered voters) or based on other frames (e.g. telephone directories). Comparing the structure frame to a list frame, a structure frame is less expensive and more convenient, but like the list frame, sampling bias and nonresponse are still possible with this method.
how to choose the right frame for your project
The size of the sample should be determined by the following considerations: The frame should be large enough to cover all units in the target population. The frame should be big enough to represent the population in terms of a reasonable number of units. The next consideration when choosing a frame is the need for updating. When information needs to be updated, there are two options available: (a) annual updating; or (b) updating as and when there is a need. Annual update would involve changing the frame at the end of each year while the latter needs updating only when there is a change in information required.
The concept of frames is considered to be an essential tool in survey research because it enhances efficiency, economy, accuracy and quality in data collection by providing a systematic way of identifying all units that meet certain criteria.
The spectrum of sampling frames can be broadly classified into two categories: (1) factor related and (2) procedure related.
Factor related surveys:
benefits of using a frame
There are many advantages of using a frame in sampling. Some of them, for example, the following, are as follows: Frame selection helps ensure that the sample is representative of the population. The sampling unit is an important consideration when determining which members of a population should be included in a survey. Each member in the sample perfectly represents one unit in the frame. Using a frame will save time and money. The frame helps to provide a representative sample among diverse populations. The frame helps to cover the entire population in statistical studies, using a representative sample from the frame. It is generally easier to manage samples if you use a frame for random sampling.