Quasi-Experimental or Non-Experimental Designs - Revision history

Ranisha at 08:50, 20 July 2018

2018-07-20T08:50:38Z

Ranisha at 08:49, 20 July 2018

2018-07-20T08:49:20Z

Ranisha at 08:48, 20 July 2018

2018-07-20T08:48:28Z

Wiki Gardener at 16:32, 6 October 2014

2014-10-06T16:32:22Z

Wiki Gardener at 13:59, 18 June 2014

2014-06-18T13:59:42Z

Fungai Cecilia Sandamu at 21:02, 4 April 2013

2013-04-04T21:02:11Z

Fungai Cecilia Sandamu at 20:55, 4 April 2013

2013-04-04T20:55:32Z

Ingmar Schlecht at 13:15, 18 February 2011

2011-02-18T13:15:34Z

Ingmar Schlecht at 13:15, 18 February 2011

2011-02-18T13:15:26Z

Rauwol mar at 12:17, 2 June 2010

2010-06-02T12:17:45Z

@@ Line 2: / Line 2: @@
 = Overview =
-'''Quasi-Experiment: '''A quasi-experimental design is an empirical study, almost like an [[Experimental Design|experimental design]] but without random assignment. Quasi-experimental designs typically allow the researcher to control the assignment to the treatment condition, but using some criterion other than random assignment (e.g., an eligibility cutoff mark). In some cases, the researcher may have control over assignment to treatment condition.<ref>Wikipedia: http://en.wikipedia.org/wiki/Quasi-experiment</ref>
+'''Quasi-Experiment: '''A quasi-experimental design is an empirical study, almost like an [[Experimental Design|experimental design]] but without random assignment. Quasi-experimental designs typically allow the researcher to control the assignment to the treatment condition but using some criterion other than random assignment (e.g., an eligibility cutoff mark). In some cases, the researcher may have control over assignment to treatment condition.<ref>Wikipedia: http://en.wikipedia.org/wiki/Quasi-experiment</ref>
 <br/>
@@ Line 39: / Line 39: @@
 <references />
 [[Category:Questionnaires_/_Interviews]]

@@ Line 12: / Line 12: @@
 = <span style="line-height: 20.390625px">Matching Methods or Constructed Controls</span> =
-Matching methods or constructed controls, in which one tries to pick an ideal comparison that matches the treatment group from a larger survey. The most widely used type of matching is propensity score matching, in which the comparison group is matched to the treatment group on the basis of a set of observed characteristics or by using the “propensity score” (predicted probability of participation given observed characteristics); the closer the propensity score, the better the match. A good comparison group comes from the same economic environment and was administered the same questionnaire by similarly trained interviewers as the treatment group.<ref name="Worldbank - http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txtfckLR">Worldbank - http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txtfckLR</ref><br/>
+Matching methods or constructed controls, in which one tries to pick an ideal comparison that matches the treatment group from a larger survey. The most widely used type of matching is propensity score matching, in which the comparison group is matched to the treatment group on the basis of a set of observed characteristics or by using the “propensity score” (predicted probability of participation given observed characteristics); the closer the propensity score, the better the match. A good comparison group comes from the same economic environment and was administered the same questionnaire by similarly trained interviewers as the treatment group.<ref name="M. Ravallion, The Mystery of the Vanishing Benefits: Ms. Speedy Analyst’s Introduction to Evaluation. The World Bank, 1999. https://bit.ly/2L7eGOh">M. Ravallion, The Mystery of the Vanishing Benefits: Ms. Speedy Analyst’s Introduction to Evaluation. The World Bank, 1999. https://bit.ly/2L7eGOh</ref><br/>
 <br/>
@@ Line 39: / Line 39: @@
 <references />
 [[Category:Impacts]]

@@ Line 2: / Line 2: @@
 = Overview =
-'''Quasi-Experiment: '''A quasi-experimental design is an empirical study, almost like an [[Experimental_Design|experimental design]] but without random assignment. Quasi-experimental designs typically allow the researcher to control the assignment to the treatment condition, but using some criterion other than random assignment (e.g., an eligibility cutoff mark). In some cases, the researcher may have control over assignment to treatment condition.<ref>Wikipedia: http://en.wikipedia.org/wiki/Quasi-experiment</ref>
+'''Quasi-Experiment: '''A quasi-experimental design is an empirical study, almost like an [[Experimental Design|experimental design]] but without random assignment. Quasi-experimental designs typically allow the researcher to control the assignment to the treatment condition, but using some criterion other than random assignment (e.g., an eligibility cutoff mark). In some cases, the researcher may have control over assignment to treatment condition.<ref>Wikipedia: http://en.wikipedia.org/wiki/Quasi-experiment</ref>
-'''Non-Experiment: '''the researcher cannot control, manipulate or alter the predictor variable or subjects, but instead, relies on interpretation, observation or interactions to come to a conclusion. Typically, this means the non-experimental researcher must rely on correlations, surveys or case studies, and cannot demonstrate a true cause-and-effect relationship. Non-experimental research tends to have a high level of external validity, meaning it can be generalized to a larger population.<ref name="Education Portal: http://education-portal.com/academy/lesson/non-experimental-and-experimental-research-differences-advantages-disadvantages.html#lesson">Education Portal: http://education-portal.com/academy/lesson/non-experimental-and-experimental-research-differences-advantages-disadvantages.html#lesson
+<br/>
-</ref>
-−
-−
 = <span style="line-height: 20.390625px">Matching Methods or Constructed Controls</span> =
@@ Line 17: / Line 16: @@
 <br/>
-= Instrumental Varialbles or Statistical Control Methods =
+= Instrumental Variables or Statistical Control Methods =
-Instrumental variables or statistical control methods, in which one uses one or more variables that matter to participation but not to outcomes given participation. This identifies the exogenous variation in outcomes attributable to the program, recognizing that its placement is not random but purposive. The “instrumental variables” are first used to predict program participation; then one sees how the outcome indicator varies with the predicted values.<ref name="Worldbank - http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txtfckLR">Worldbank - http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txtfckLR</ref><br/>
+Instrumental variables or statistical control methods, in which one uses one or more variables that matter to participation but not to outcomes given participation. This identifies the exogenous variation in outcomes attributable to the program, recognizing that its placement is not random but purposive. The “instrumental variables” are first used to predict program participation; then one sees how the outcome indicator varies with the predicted values.<ref name="M. Ravallion, The Mystery of the Vanishing Benefits: Ms. Speedy Analyst’s Introduction to Evaluation. The World Bank, 1999. https://bit.ly/2L7eGOh">M. Ravallion, The Mystery of the Vanishing Benefits: Ms. Speedy Analyst’s Introduction to Evaluation. The World Bank, 1999. https://bit.ly/2L7eGOh</ref><br/>
 <br/>
@@ Line 25: / Line 24: @@
 = Reflexive Comparisons =
-Reflexive comparisons, in which a baseline survey of participants is done before the intervention and a follow-up survey is done after. The baseline provides the comparison group, and impact is measured by the change in outcome indicators before and after the intervention.<ref name="Worldbank - http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txtfckLR">Worldbank - http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txtfckLR</ref><br/>
+Reflexive comparisons, in which a baseline survey of participants is done before the intervention and a follow-up survey is done after. The baseline provides the comparison group, and impact is measured by the change in outcome indicators before and after the intervention.<ref name="M. Ravallion, The Mystery of the Vanishing Benefits: Ms. Speedy Analyst’s Introduction to Evaluation. The World Bank, 1999. https://bit.ly/2L7eGOh">M. Ravallion, The Mystery of the Vanishing Benefits: Ms. Speedy Analyst’s Introduction to Evaluation. The World Bank, 1999. https://bit.ly/2L7eGOh</ref><br/>
 <br/>
@@ Line 40: / Line 39: @@
 <references />
 [[Category:Questionnaires_/_Interviews]]

@@ Line 1: / Line 1: @@
 = Overview =
@@ Line 6: / Line 13: @@
 = <span style="line-height: 20.390625px">Matching Methods or Constructed Controls</span> =
-Matching methods or constructed controls, in which one tries to pick an ideal comparison that matches the treatment group from a larger survey. The most widely used type of matching is propensity score matching, in which the comparison group is matched to the treatment group on the basis of a set of observed characteristics or by using the “propensity score” (predicted probability of participation given observed characteristics); the closer the propensity score, the better the match. Agood comparison group comes from the same economic environment and was administered the same questionnaire by similarly trained interviewers as the treatment group.<ref name="Worldbank - http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txtfckLR">Worldbank - http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txtfckLR</ref><br/>
+Matching methods or constructed controls, in which one tries to pick an ideal comparison that matches the treatment group from a larger survey. The most widely used type of matching is propensity score matching, in which the comparison group is matched to the treatment group on the basis of a set of observed characteristics or by using the “propensity score” (predicted probability of participation given observed characteristics); the closer the propensity score, the better the match. A good comparison group comes from the same economic environment and was administered the same questionnaire by similarly trained interviewers as the treatment group.<ref name="Worldbank - http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txtfckLR">Worldbank - http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txtfckLR</ref><br/>
 <br/>
@@ Line 12: / Line 19: @@
 = Instrumental Varialbles or Statistical Control Methods =
-''Instrumental variables or statistical control ''methods, in which one uses one or more variables that matter to participation but not to outcomes given participation. This identifies the exogenous variation in outcomes attributable to the program, recognizing that its placement is not random but purposive. The “instrumental variables” are first used to predict program participation; then one sees how the outcome indicator varies with the predicted values.<ref name="Worldbank - http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txtfckLR">Worldbank - http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txtfckLR</ref><br/>
+Instrumental variables or statistical control methods, in which one uses one or more variables that matter to participation but not to outcomes given participation. This identifies the exogenous variation in outcomes attributable to the program, recognizing that its placement is not random but purposive. The “instrumental variables” are first used to predict program participation; then one sees how the outcome indicator varies with the predicted values.<ref name="Worldbank - http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txtfckLR">Worldbank - http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txtfckLR</ref><br/>
 <br/>
@@ Line 24: / Line 31: @@
 = Further Information =
-*[[Experimental_Design|Experimental Design]]
+*[[Experimental Design|Experimental Design]]
 <br/>
@@ Line 33: / Line 41: @@
 [[Category:Impacts]]

@@ Line 1: / Line 1: @@
-= <span style="line-height: 20.390625px;">Matching Methods or Constructed Controls</span> =
+= Overview =
-''Matching methods or constructed controls'', in which one tries to pick an ideal comparison that matches the treatment group from a larger survey. The most widely used type of matching is ''propensity score matching'', in which the comparison group is matched to the treatment group on the basis of a set of observed characteristics or by using the “propensity score” (predicted probability of participation given observed characteristics); the closer the propensity score, the better the match. Agood comparison group comes from the same economic environment and was administered the same questionnaire by similarly trained interviewers as the treatment group.<ref name="Worldbank - http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txtfckLR">Worldbank - http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txtfckLR</ref><br/>
 <br/>
@@ Line 14: / Line 18: @@
 = Reflexive Comparisons =
-''Reflexive comparisons'', in which a baseline survey of participants is done before the intervention and a follow-up survey is done after. The baseline provides the comparison group, and impact is measured by the change in outcome indicators before and after the intervention.<ref name="Worldbank - http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txtfckLR">Worldbank - http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txtfckLR</ref><br/>
+Reflexive comparisons, in which a baseline survey of participants is done before the intervention and a follow-up survey is done after. The baseline provides the comparison group, and impact is measured by the change in outcome indicators before and after the intervention.<ref name="Worldbank - http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txtfckLR">Worldbank - http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txtfckLR</ref><br/>
 <br/>
 = Further Information =
 <br/>

← Older revision		Revision as of 20:55, 4 April 2013
Line 1:		Line 1:
−	*<span style="font-size: 10pt;"><font face="Arial">''Matching methods or constructed controls'', in which one tries to pick an ideal comparison that matches the treatment group from a larger survey. The most widely used type of matching is ''propensity score matching'', in which the comparison group is matched to the treatment group on the basis of a set of observed characteristics or by using the “propensity score” (predicted probability of </font></span><span style="font-size: 10pt;"><font face="Arial">participation given observed characteristics); the closer the propensity score, the better the match. Agood comparison group comes from the same economic environment and was administered the same questionnaire by similarly trained interviewers as the treatment group.<ref name="worldbank">http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txt</ref></font></span>
−	*<span style="font-size: 10pt;"><font face="Arial">''Double difference or difference-in-differences ''methods, in which one compares a treatment and comparison group (first difference) before and after a program (second difference). Comparators </font></span><span style="font-size: 10pt;"><font face="Arial">should be dropped when propensity scores are used and if they have scores outside the range observed for the treatment group.<ref name="worldbank" /></font></span>
−	*<span style="font-size: 10pt;"><font face="Arial">''Instrumental variables or statistical control ''methods, in which one uses one or more variables that matter to participation but not to outcomes given participation. This identifies the exogenous variation </font></span><span style="font-size: 10pt;"><font face="Arial">in outcomes attributable to the program, recognizing that its placement is not random but purposive. The “instrumental variables” are first used to predict program participation; then one sees how the outcome indicator varies with the predicted values.<ref name="worldbank" /></font></span>
−	*<span style="font-size: 10pt;"><font face="Arial">''Reflexive comparisons'', in which a baseline survey of participants is done before the intervention and a follow-up survey is done after. The baseline provides the comparison group, and impact is measured by the change in outcome indicators before and after the intervention.<ref name="worldbank" /></font></span>

−	~~[[Category~~:~~Impacts]]~~	+	= <span style="line-height: 20.390625px;">Matching Methods or Constructed Controls</span> =
		+
		+	''Matching methods or constructed controls'', in which one tries to pick an ideal comparison that matches the treatment group from a larger survey. The most widely used type of matching is ''propensity score matching'', in which the comparison group is matched to the treatment group on the basis of a set of observed characteristics or by using the “propensity score” (predicted probability of participation given observed characteristics); the closer the propensity score, the better the match. Agood comparison group comes from the same economic environment and was administered the same questionnaire by similarly trained interviewers as the treatment group.<ref name="worldbank">http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txtfckLR*''Double difference or difference-in-differences ''methods, in which one compares a treatment and comparison group (first difference) before and after a program (second difference). Comparatorsshould be dropped when propensity scores are used and if they have scores outside the range observed for the treatment group.<ref name="worldbank">_</ref><br/>
		+
		+	<br/>
		+
		+	= Instrumental Varialbles or Statistical Control Methods =
		+
		+	''Instrumental variables or statistical control ''methods, in which one uses one or more variables that matter to participation but not to outcomes given participation. This identifies the exogenous variation in outcomes attributable to the program, recognizing that its placement is not random but purposive. The “instrumental variables” are first used to predict program participation; then one sees how the outcome indicator varies with the predicted values.<ref name="worldbank">_</ref><br/>
		+
		+	<br/>
		+
		+	= Reflexive Comparisons =
		+
		+	''Reflexive comparisons'', in which a baseline survey of participants is done before the intervention and a follow-up survey is done after. The baseline provides the comparison group, and impact is measured by the change in outcome indicators before and after the intervention.<ref name="worldbank">_</ref><br/>
		+
		+	<br/>
		+
		+	= Further Information =
		+
		+	<br/>
		+
		+	= References =

	<references />		<references />
		+
		+	[[Category:Impacts]]

← Older revision		Revision as of 13:15, 18 February 2011
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	[[Category:Impacts]]		[[Category:Impacts]]
		+
		+	<references />

@@ Line 1: / Line 1: @@
-*<span style="font-size: 10pt; mso-bidi-font-family: arial"><font face="Arial">''Matching methods or constructed controls'', in which one tries to pick an ideal comparison that matches the treatment group from a larger survey. The most widely used type of matching is ''propensity score matching'', in which the comparison group is matched to the treatment group on the basis of a set of observed characteristics or by using the “propensity score” (predicted probability of </font></span><span style="font-size: 10pt; mso-bidi-font-family: arial"><font face="Arial">participation given observed characteristics); the closer the propensity score, the better the match. Agood comparison group comes from the same economic environment and was administered the same questionnaire by similarly trained interviewers as the treatment group.</font></span>
+*<span style="font-size: 10pt;"><font face="Arial">''Matching methods or constructed controls'', in which one tries to pick an ideal comparison that matches the treatment group from a larger survey. The most widely used type of matching is ''propensity score matching'', in which the comparison group is matched to the treatment group on the basis of a set of observed characteristics or by using the “propensity score” (predicted probability of </font></span><span style="font-size: 10pt;"><font face="Arial">participation given observed characteristics); the closer the propensity score, the better the match. Agood comparison group comes from the same economic environment and was administered the same questionnaire by similarly trained interviewers as the treatment group.<ref name="worldbank">http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2000/08/19/000094946_00080705302127/Rendered/INDEX/multi_page.txt</ref></font></span>
-*<span style="font-size: 10pt; mso-bidi-font-family: arial"><font face="Arial">''Double difference or difference-in-differences ''methods, in which one compares a treatment and comparison group (first difference) before and after a program (second difference). Comparators </font></span><span style="font-size: 10pt; mso-bidi-font-family: arial"><font face="Arial">should be dropped when propensity scores are used and if they have scores outside the range observed for the treatment group.</font></span>
+*<span style="font-size: 10pt;"><font face="Arial">''Double difference or difference-in-differences ''methods, in which one compares a treatment and comparison group (first difference) before and after a program (second difference). Comparators </font></span><span style="font-size: 10pt;"><font face="Arial">should be dropped when propensity scores are used and if they have scores outside the range observed for the treatment group.<ref name="worldbank" /></font></span>
-*<span style="font-size: 10pt; mso-bidi-font-family: arial"><font face="Arial">''Instrumental variables or statistical control ''methods, in which one uses one or more variables that matter to participation but not to outcomes given participation. This identifies the exogenous variation </font></span><span style="font-size: 10pt; mso-bidi-font-family: arial"><font face="Arial">in outcomes attributable to the program, recognizing that its placement is not random but purposive. The “instrumental variables” are first used to predict program participation; then one sees how the outcome indicator varies with the predicted values.</font></span>
+*<span style="font-size: 10pt;"><font face="Arial">''Instrumental variables or statistical control ''methods, in which one uses one or more variables that matter to participation but not to outcomes given participation. This identifies the exogenous variation </font></span><span style="font-size: 10pt;"><font face="Arial">in outcomes attributable to the program, recognizing that its placement is not random but purposive. The “instrumental variables” are first used to predict program participation; then one sees how the outcome indicator varies with the predicted values.<ref name="worldbank" /></font></span>
-*<span style="font-size: 10pt; mso-bidi-font-family: arial"><font face="Arial">''Reflexive comparisons'', in which a baseline survey of participants is done before the intervention and a follow-up survey is done after. The baseline provides the comparison group, and impact is measured by the change in outcome indicators before and after the intervention.</font></span>
+*<span style="font-size: 10pt;"><font face="Arial">''Reflexive comparisons'', in which a baseline survey of participants is done before the intervention and a follow-up survey is done after. The baseline provides the comparison group, and impact is measured by the change in outcome indicators before and after the intervention.<ref name="worldbank" /></font></span>
 [[Category:Impacts]]

← Older revision		Revision as of 12:17, 2 June 2010
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	*<span style="font-size: 10pt; mso-bidi-font-family: arial"><font face="Arial">''Reflexive comparisons'', in which a baseline survey of participants is done before the intervention and a follow-up survey is done after. The baseline provides the comparison group, and impact is measured by the change in outcome indicators before and after the intervention.</font></span>		*<span style="font-size: 10pt; mso-bidi-font-family: arial"><font face="Arial">''Reflexive comparisons'', in which a baseline survey of participants is done before the intervention and a follow-up survey is done after. The baseline provides the comparison group, and impact is measured by the change in outcome indicators before and after the intervention.</font></span>

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