Guidelines for Sampling/ Selection Criterias - Revision history

Wiki Gardener at 10:02, 8 August 2014

2014-08-08T10:02:14Z

Ranisha at 14:46, 22 July 2014

2014-07-22T14:46:57Z

Ranisha at 14:22, 22 July 2014

2014-07-22T14:22:22Z

Ranisha at 14:12, 22 July 2014

2014-07-22T14:12:16Z

Özlem Yasemin Taskin at 08:51, 7 August 2013

2013-08-07T08:51:44Z

Katharina Wiedemann at 14:54, 17 May 2012

2012-05-17T14:54:32Z

Katharina Wiedemann at 07:28, 17 May 2012

2012-05-17T07:28:50Z

Rauwol mar at 12:06, 2 June 2010

2010-06-02T12:06:25Z

Robert at 14:49, 27 January 2010

2010-01-27T14:49:11Z

Intern at 10:09, 28 October 2009

2009-10-28T10:09:03Z

@@ Line 1: / Line 1: @@
-= Introduction =
+= Overview =
 The purpose of '''sampling '''is to reduce the cost of collecting data about a population by gathering information from a subset instead of the entire population. While the optimal sampling procedure is heavily case-dependent, guidance and “rules of thumb” exist.
@@ Line 12: / Line 12: @@
 A statistically accurate determination of the required sample size mainly depends on the study’s measurement objective, which is in most cases the examination of changes in specific indicators (e.g. [[Cooking with Firewood|firewood consumption]], studying hours) over time or differences in these indicators between project and control areas.
-<u>Technically, the '''required sample size '''for a given indicator'''for each household survey round and / or comparison group '''depends on five factors:</u>
 #the number of households in the target population
 #the initial or baseline level of the indicator (e.g. fuelwood consumption before the intervention)
@@ Line 18: / Line 20: @@
 #the degree of confidence with which it is desired to be certain that an observed change would not have occurred by chance (the level of statistical significance), and
 #the degree of confidence with which it is desired to be certain that an actual change of the magnitude specified above will be detected (statistical power).
 <br/>
-The first two are given by the '''characteristics of the population '''in the target region, while the last three are determined by the '''researcher'''. Sample size formulas and “rules of thumb” exist to determine concrete sample size figures based on this information (see for example Magnani 1997[[#ftn1|[1]).]]
+<u>Another more pragmatic approach concerning sample size decisions is to somehow invert this procedure: </u>
-Since '''non-response''' in surveys, particularly in developing countries, can never be ruled out, it has to be considered during the calculation of sample size requirements as well. An allowance of 10 percent should prove adequate in most situations.
+Since non-response in surveys, particularly in developing countries, can never be ruled out, it has to be considered during the calculation of sample size requirements as well. An allowance of 10% should prove adequate in most situations.
 <br/>
@@ Line 33: / Line 37: @@
 = Selection of Sample Households =
-Once overall sample size requirements have been determined, the final step in developing the sample design is to determine how many '''clusters '''(e.g. villages) and how many '''households per cluster '''should be chosen. While smaller clusters imply higher sampling precision, they also imply higher survey costs due to higher costs of transporting and sustaining field staff. 20 interviews per cluster represent an adequate solution for this trade-off.
+Once overall sample size requirements have been determined, the final step in developing the sample design is to determine how many '''clusters '''(e.g. villages) and how many households per cluster should be chosen. While smaller clusters imply higher sampling precision, they also imply higher survey costs due to higher costs of transporting and sustaining field staff. 20 interviews per cluster represent an adequate solution for this trade-off.
 Whatever the sample size, the '''randomness of sample selection''' is crucial for guaranteeing representativeness of the collected data. Different easy-to-implement alternatives exist such as segmentation and '''random-walk methods''' where the first household to be interviewed is drawn randomly. The enumerators then simply select every 5th household, for example.
@@ Line 45: / Line 49: @@
 *[[Theory Based Approach|Theory Based Approach]]<br/>
 *[[Control Groups|Control Groups]]
-*[[Portal:Impacts|Portal:Impacts]]<br/>
+*[[Portal:Impacts|Impact Portal on energypedia]]<br/>
 = Reference =
 *Source: RWI (2009)
 [[Category:Impacts]]

@@ Line 43: / Line 43: @@
 = Further Information =
-*[[Theory_Based_Approach|Theory Based Approach]]<br/>
+*[[Theory Based Approach|Theory Based Approach]]<br/>
-*[[Control_Groups|Control Groups]]
+*[[Control Groups|Control Groups]]
 = Reference =
@@ Line 54: / Line 55: @@
 <br/>
 [[Category:Questionnaires_/_Interviews]]

@@ Line 10: / Line 10: @@
 A total of some '''100 interviews '''is generally an adequate guess for sample sizes that allow making reasonable statistical inferences even for subgroups of the surveyed population such as [[Portal:Grid|grid-connected households]]. If it is intended to compare subgroups, for example electrified and non-electrified households, the sample size per subgroup must not fall below 30 households.
-A statistically accurate determination of the required sample size mainly depends on the study’s measurement objective, which is in most cases the examination of changes in specific indicators (e.g. [[Cooking_with_Firewood|firewood consumption]], studying hours) over time or differences in these indicators between project and control areas.
+A statistically accurate determination of the required sample size mainly depends on the study’s measurement objective, which is in most cases the examination of changes in specific indicators (e.g. [[Cooking with Firewood|firewood consumption]], studying hours) over time or differences in these indicators between project and control areas.
 <u>Technically, the '''required sample size '''for a given indicator'''for each household survey round and / or comparison group '''depends on five factors:</u>
@@ Line 40: / Line 40: @@
 <br/>
 = Reference =
@@ Line 49: / Line 54: @@
 <br/>
 [[Category:Impacts]]

@@ Line 4: / Line 4: @@
 The purpose of '''sampling '''is to reduce the cost of collecting data about a population by gathering information from a subset instead of the entire population. While the optimal sampling procedure is heavily case-dependent, guidance and “rules of thumb” exist.
+<br/>
 = Factors Influencing Sample Size Decisions =
-A total of some '''100 interviews '''is generally an adequate guess for sample sizes that allow making reasonable statistical inferences even for subgroups of the surveyed population such as grid-connected households. If it is intended to compare subgroups, for example electrified and non-electrified households, the sample size per subgroup must not fall below 30 households.
+A total of some '''100 interviews '''is generally an adequate guess for sample sizes that allow making reasonable statistical inferences even for subgroups of the surveyed population such as [[Portal:Grid|grid-connected households]]. If it is intended to compare subgroups, for example electrified and non-electrified households, the sample size per subgroup must not fall below 30 households.
-A statistically accurate determination of the required sample size mainly depends on the study’s measurement objective, which is in most cases the examination of changes in specific indicators (e.g. firewood consumption, studying hours) over time or differences in these indicators between project and control areas.
+A statistically accurate determination of the required sample size mainly depends on the study’s measurement objective, which is in most cases the examination of changes in specific indicators (e.g. [[Cooking_with_Firewood|firewood consumption]], studying hours) over time or differences in these indicators between project and control areas.
 <u>Technically, the '''required sample size '''for a given indicator'''for each household survey round and / or comparison group '''depends on five factors:</u>
 #the number of households in the target population
 #the initial or baseline level of the indicator (e.g. fuelwood consumption before the intervention)
 #the magnitude of change expected to be reliably measured (e.g. 50 percent fuel savings for improved stoves in comparison to traditional stoves)
 #the degree of confidence with which it is desired to be certain that an observed change would not have occurred by chance (the level of statistical significance), and
 #the degree of confidence with which it is desired to be certain that an actual change of the magnitude specified above will be detected (statistical power).
@@ Line 29: / Line 29: @@
 Since '''non-response''' in surveys, particularly in developing countries, can never be ruled out, it has to be considered during the calculation of sample size requirements as well. An allowance of 10 percent should prove adequate in most situations.
+<br/>
 = Selection of Sample Households =
 Once overall sample size requirements have been determined, the final step in developing the sample design is to determine how many '''clusters '''(e.g. villages) and how many '''households per cluster '''should be chosen. While smaller clusters imply higher sampling precision, they also imply higher survey costs due to higher costs of transporting and sustaining field staff. 20 interviews per cluster represent an adequate solution for this trade-off.
 Whatever the sample size, the '''randomness of sample selection''' is crucial for guaranteeing representativeness of the collected data. Different easy-to-implement alternatives exist such as segmentation and '''random-walk methods''' where the first household to be interviewed is drawn randomly. The enumerators then simply select every 5th household, for example.
@@ Line 39: / Line 39: @@
 In the optimal case, sample households are selected '''by means''' of a list of all households located within each cluster (e.g. from census enumerations). A sample of units is then chosen using either simple random or systematic sampling. In most cases, though, such lists are not available. Conducting pre-surveys for an enumeration of households is likely to be unacceptably costly and time consuming.
+<br/>
 = Reference =
-Source: RWI (2009)
+*Source: RWI (2009)
 <div>
-[[#ftnref1|[1]]] <span>Magnani, Robert (1997). Sampling Guide. Food and Nutrition Technical Assistance Project (FANTA), Washington, D.C.</span>
+*[[#ftnref1|[1]]] <span>Magnani, Robert (1997). Sampling Guide. Food and Nutrition Technical Assistance Project (FANTA), Washington, D.C.</span>
 </div>
 [[Category:Questionnaires_/_Interviews]]

@@ Line 1: / Line 1: @@
-= Introduction <br/> =
 The purpose of '''sampling '''is to reduce the cost of collecting data about a population by gathering information from a subset instead of the entire population. While the optimal sampling procedure is heavily case-dependent, guidance and “rules of thumb” exist.
@@ Line 5: / Line 6: @@
-= Factors Influencing Sample Size Decisions<br/> =
+= Factors Influencing Sample Size Decisions =
-A total of some '''100 interviews '''is generally an adequate guess for sample sizes that allow making reasonable statistical inferences even for subgroups of the surveyed population such as grid-connected households. If it is intended to compare subgroups, for example electrified and non-electrified households, the sample size per subgroup must not fall below 30 households.&nbsp;
+A total of some '''100 interviews '''is generally an adequate guess for sample sizes that allow making reasonable statistical inferences even for subgroups of the surveyed population such as grid-connected households. If it is intended to compare subgroups, for example electrified and non-electrified households, the sample size per subgroup must not fall below 30 households.
 A statistically accurate determination of the required sample size mainly depends on the study’s measurement objective, which is in most cases the examination of changes in specific indicators (e.g. firewood consumption, studying hours) over time or differences in these indicators between project and control areas.
 <u>Technically, the '''required sample size '''for a given indicator'''for each household survey round and / or comparison group '''depends on five factors:</u>
 #the number of households in the target population
 #the initial or baseline level of the indicator (e.g. fuelwood consumption before the intervention)
-#the magnitude of change expected to be reliably measured (e.g. 50 percent fuel savings for improved stoves in comparison to traditional stoves)&nbsp;
+#the magnitude of change expected to be reliably measured (e.g. 50 percent fuel savings for improved stoves in comparison to traditional stoves)
 #the degree of confidence with which it is desired to be certain that an observed change would not have occurred by chance (the level of statistical significance), and
 #the degree of confidence with which it is desired to be certain that an actual change of the magnitude specified above will be detected (statistical power).
-The first two are given by the '''characteristics of the population '''in the target region, while the last three are determined by the '''researcher'''. Sample size formulas and “rules of thumb” exist to determine concrete sample size figures based on this information (see for example Magnani 1997[[#ftn1|<span><span><span><span>[1]</span></span></span></span><span>).</span>]]
+<br/>
 Another more '''pragmatic approach''' concerning sample size decisions is to somehow invert this procedure: the potential sample size is established according to the '''survey budget '''in order to determine 3), 4), 5), the explanatory power to be expected from the survey. In case the explanatory power turns out to be higher or lower than desired, smaller adjustments may be made either at the budget or the sample size.
@@ Line 31: / Line 31: @@
-= Selection of Sample Households<br/> =
+= Selection of Sample Households =
-Once overall sample size requirements have been determined, the final step in developing the sample design is to determine how many '''clusters '''(e.g. villages) and how many '''households per cluster '''should be chosen. While smaller clusters imply higher sampling precision, they also imply higher survey costs due to higher costs of transporting and sustaining field staff. 20 interviews per cluster represent an adequate solution for this trade-off.&nbsp;
+Once overall sample size requirements have been determined, the final step in developing the sample design is to determine how many '''clusters '''(e.g. villages) and how many '''households per cluster '''should be chosen. While smaller clusters imply higher sampling precision, they also imply higher survey costs due to higher costs of transporting and sustaining field staff. 20 interviews per cluster represent an adequate solution for this trade-off.
 Whatever the sample size, the '''randomness of sample selection''' is crucial for guaranteeing representativeness of the collected data. Different easy-to-implement alternatives exist such as segmentation and '''random-walk methods''' where the first household to be interviewed is drawn randomly. The enumerators then simply select every 5th household, for example.
@@ Line 41: / Line 41: @@
-= Reference<br/> =
+= Reference =
 Source: RWI (2009)
 <div>
-[[#ftnref1|<span><span><span>[1]</span></span></span>]] <span>Magnani, Robert (1997). Sampling Guide. Food and Nutrition Technical Assistance Project (FANTA), Washington, D.C.</span>
+[[#ftnref1|[1]]] <span>Magnani, Robert (1997). Sampling Guide. Food and Nutrition Technical Assistance Project (FANTA), Washington, D.C.</span>
 </div>
 [[Category:Impacts]]

@@ Line 1: / Line 1: @@
-===== '''Sampling'''  =====
+= '''Introduction '''<br/> =
-The purpose of sampling is to reduce the cost of collecting data about a population by gathering information from a subset instead of the entire population. While the optimal sampling procedure is heavily case-dependent, guidance and “rules of thumb” exist.
+The purpose of '''sampling '''is to reduce the cost of collecting data about a population by gathering information from a subset instead of the entire population. While the optimal sampling procedure is heavily case-dependent, guidance and “rules of thumb” exist.
-A statistically accurate determination of the required sample size mainly depends on the study’s measurement objective, which is in most cases the examination of changes in specific indicators (e.g. firewood consumption, studying hours) over time or differences in these indicators between project and control areas.
+= '''Factors Influencing Sample Size Decisions'''<br/> =
-Technically, the '''required sample size '''for a given indicator'''for each household survey round and/ or comparison group '''depends on five factors:
+A total of some '''100 interviews '''is generally an adequate guess for sample sizes that allow making reasonable statistical inferences even for subgroups of the surveyed population such as grid-connected households. If it is intended to compare subgroups, for example electrified and non-electrified households, the sample size per subgroup must not fall below 30 households.&nbsp;
-#the number of households in the target population&nbsp;
+A statistically accurate determination of the required sample size mainly depends on the study’s measurement objective, which is in most cases the examination of changes in specific indicators (e.g. firewood consumption, studying hours) over time or differences in these indicators between project and control areas.
-The first''two'' are given by the '''characteristics of the population '''in the target region, while the last ''three'' are determined by the '''researcher'''. Sample size formulas and “rules of thumb” exist to determine concrete sample size figures based on this information (see for example Magnani 1997[[#_ftn1|<span><span><span><span>[1]</span></span></span></span><span>).</span>]]
+<u>Technically, the '''required sample size '''for a given indicator'''for each household survey round and / or comparison group '''depends on five factors:<br/></u>
-<br>
+#the number of households in the target population&nbsp;
-===== '''Selection of sample households'''  =====
+The first two are given by the '''characteristics of the population '''in the target region, while the last three are determined by the '''researcher'''. Sample size formulas and “rules of thumb” exist to determine concrete sample size figures based on this information (see for example Magnani 1997[[#ftn1|<span><span><span><span>[1]</span></span></span></span><span>).</span>]]
-In the optimal case, sample households are selected '''by means''' of a list of all households located within each cluster (e.g. from census enumerations). A sample of units is then chosen using either simple random or systematic sampling. In most cases, though, such lists are not available. Conducting pre-surveys for an enumeration of households is likely to be unacceptably costly and time consuming.
+Another more '''pragmatic approach''' concerning sample size decisions is to somehow invert this procedure: the potential sample size is established according to the '''survey budget '''in order to determine 3), 4), 5), the explanatory power to be expected from the survey. In case the explanatory power turns out to be higher or lower than desired, smaller adjustments may be made either at the budget or the sample size.
-<br>
+Since '''non-response''' in surveys, particularly in developing countries, can never be ruled out, it has to be considered during the calculation of sample size requirements as well. An allowance of 10 percent should prove adequate in most situations.
-''Source: RWI (2009)''
 <div>
-''[[#_ftnref1|<span><span><span>[1]</span></span></span>]] <span>Magnani, Robert (1997). Sampling Guide. Food and Nutrition Technical Assistance Project (FANTA), Washington, D.C.</span>''
+[[#ftnref1|<span><span><span>[1]</span></span></span>]] <span>Magnani, Robert (1997). Sampling Guide. Food and Nutrition Technical Assistance Project (FANTA), Washington, D.C.</span>
 </div>
 [[Category:Impacts]]

← Older revision		Revision as of 12:06, 2 June 2010
Line 40:		Line 40:
	</div>		</div>

−	[[Category:~~Monitoring~~]]	+	[[Category:Impacts]]

← Older revision		Revision as of 14:49, 27 January 2010
Line 39:		Line 39:
	''[[#_ftnref1\|<span><span><span>[1]</span></span></span>]] <span>Magnani, Robert (1997). Sampling Guide. Food and Nutrition Technical Assistance Project (FANTA), Washington, D.C.</span>''		''[[#_ftnref1\|<span><span><span>[1]</span></span></span>]] <span>Magnani, Robert (1997). Sampling Guide. Food and Nutrition Technical Assistance Project (FANTA), Washington, D.C.</span>''
	</div>		</div>
		+
		+	[[Category:Monitoring]]