Journal of speech, language, and hearing research : JSLHR, 1999
Contemporary investigators in the areas of speech, language, and hearing rely heavily on inferent... more Contemporary investigators in the areas of speech, language, and hearing rely heavily on inferential statistical procedures to answer both basic and applied research questions. Such statistical procedures typically involve a number of assumptions that need to be fulfilled in order for the procedure to be appropriate for a specific data set. Unfortunately, a review of recent publications in the Journal of Speech, Language, and Hearing Research indicated that some pivotal issues related to those underlying assumptions, although widely discussed and emphasized in the statistical literature, often appear to be neglected in these fields of research. This tutorial therefore addresses two issues that are particularly important for an appropriate and accurate use of some of the most commonly used statistical procedures. The first issue concerns the importance of addressing the sphericity assumption in studies with a repeated measures design. The second issue concerns the definition of the e...
In this study, we examine to what extent psychosocial student outcomes in primary school children... more In this study, we examine to what extent psychosocial student outcomes in primary school children vary between classes, and whether elements of teaching can explain some of this variation. Starting with a sample of 379 kindergarten children out of 24 classes, academic achievement and behaviour problems were assessed in 2 consecutive years. Additionally, a set of teaching characteristics was measured
For 39 controlled studies on the analgesic effect of antidepressants, a meta-analysis was conduct... more For 39 controlled studies on the analgesic effect of antidepressants, a meta-analysis was conducted to get an estimation of the effect size, and to obtain a sight on the possible modes of action and the methodology used. The mean size of the analgesic effect was 0.64. It means that the average chronic pain patient who received an antidepressant treatment had less pain than 74% of the chronic pain patients who received a placebo. This quantification, however, is only as good as the studies on which it is based, and it could be differentiated for each of the pain syndromes and antidepressants examined. Real analgesic qualities of antidepressive agents seemed to offer the most plausible and economical explanation for the effect, but the predominant importance of serotonin reuptake blocking was not confirmed. Finally, the meta-analysis appeared to be fruitful for the generation of new hypotheses, for making some recommendations for future research, and for proposing some provisional guidelines for the clinical use of antidepressants in chronic non-malignant pain.
Interest in combining probabilities has a long history in the global statistical community. The f... more Interest in combining probabilities has a long history in the global statistical community. The first steps in this direction were taken by Ronald Fisher, who introduced the idea of combining p-values of independent tests to provide a global decision rule when multiple aspects of a given problem were of interest. An interesting approach to this idea of combining p-values is the one based on permutation theory. The methods belonging to this particular approach exploit the permutation distributions of the tests to be combined, and use a simple function to combine probabilities. Combining p-values finds a very interesting application in the analysis of replicated single-case experiments. In this field the focus, while comparing different treatments effects, is more articulated than when just looking at the means of the different populations. Moreover, it is often of interest to combine the results obtained on the single patients in order to get more global information about the phenomenon under study. This paper gives an overview of how the concept of combining p-values was conceived, and how it can be easily handled via permutation techniques. Finally, the method of combining p-values is applied to a simulated replicated single-case experiment, and a numerical illustration is presented.
Single-case experiments can be used to evaluate the effect of an intervention or treatment for a ... more Single-case experiments can be used to evaluate the effect of an intervention or treatment for a single entity. The internal validity and statistical conclusion validity of single-case experiments can be improved by incorporating randomisation in their design. In this article, we explain how to design randomised single-case phase and alternation studies as well as randomised simultaneous and sequential replication studies, and how to conduct randomisation tests for these designs. Advantages and limitations of randomisation tests are discussed. In order to not only determine the (non)randomness of an intervention effect, but also the magnitude of this effect, we propose to use an effect size index as a test statistic for the randomisation test. We illustrate this combination for the design and analysis of an ABAB phase study, using a free software package.
Journal of speech, language, and hearing research : JSLHR, 1999
Contemporary investigators in the areas of speech, language, and hearing rely heavily on inferent... more Contemporary investigators in the areas of speech, language, and hearing rely heavily on inferential statistical procedures to answer both basic and applied research questions. Such statistical procedures typically involve a number of assumptions that need to be fulfilled in order for the procedure to be appropriate for a specific data set. Unfortunately, a review of recent publications in the Journal of Speech, Language, and Hearing Research indicated that some pivotal issues related to those underlying assumptions, although widely discussed and emphasized in the statistical literature, often appear to be neglected in these fields of research. This tutorial therefore addresses two issues that are particularly important for an appropriate and accurate use of some of the most commonly used statistical procedures. The first issue concerns the importance of addressing the sphericity assumption in studies with a repeated measures design. The second issue concerns the definition of the e...
In this study, we examine to what extent psychosocial student outcomes in primary school children... more In this study, we examine to what extent psychosocial student outcomes in primary school children vary between classes, and whether elements of teaching can explain some of this variation. Starting with a sample of 379 kindergarten children out of 24 classes, academic achievement and behaviour problems were assessed in 2 consecutive years. Additionally, a set of teaching characteristics was measured
For 39 controlled studies on the analgesic effect of antidepressants, a meta-analysis was conduct... more For 39 controlled studies on the analgesic effect of antidepressants, a meta-analysis was conducted to get an estimation of the effect size, and to obtain a sight on the possible modes of action and the methodology used. The mean size of the analgesic effect was 0.64. It means that the average chronic pain patient who received an antidepressant treatment had less pain than 74% of the chronic pain patients who received a placebo. This quantification, however, is only as good as the studies on which it is based, and it could be differentiated for each of the pain syndromes and antidepressants examined. Real analgesic qualities of antidepressive agents seemed to offer the most plausible and economical explanation for the effect, but the predominant importance of serotonin reuptake blocking was not confirmed. Finally, the meta-analysis appeared to be fruitful for the generation of new hypotheses, for making some recommendations for future research, and for proposing some provisional guidelines for the clinical use of antidepressants in chronic non-malignant pain.
Interest in combining probabilities has a long history in the global statistical community. The f... more Interest in combining probabilities has a long history in the global statistical community. The first steps in this direction were taken by Ronald Fisher, who introduced the idea of combining p-values of independent tests to provide a global decision rule when multiple aspects of a given problem were of interest. An interesting approach to this idea of combining p-values is the one based on permutation theory. The methods belonging to this particular approach exploit the permutation distributions of the tests to be combined, and use a simple function to combine probabilities. Combining p-values finds a very interesting application in the analysis of replicated single-case experiments. In this field the focus, while comparing different treatments effects, is more articulated than when just looking at the means of the different populations. Moreover, it is often of interest to combine the results obtained on the single patients in order to get more global information about the phenomenon under study. This paper gives an overview of how the concept of combining p-values was conceived, and how it can be easily handled via permutation techniques. Finally, the method of combining p-values is applied to a simulated replicated single-case experiment, and a numerical illustration is presented.
Single-case experiments can be used to evaluate the effect of an intervention or treatment for a ... more Single-case experiments can be used to evaluate the effect of an intervention or treatment for a single entity. The internal validity and statistical conclusion validity of single-case experiments can be improved by incorporating randomisation in their design. In this article, we explain how to design randomised single-case phase and alternation studies as well as randomised simultaneous and sequential replication studies, and how to conduct randomisation tests for these designs. Advantages and limitations of randomisation tests are discussed. In order to not only determine the (non)randomness of an intervention effect, but also the magnitude of this effect, we propose to use an effect size index as a test statistic for the randomisation test. We illustrate this combination for the design and analysis of an ABAB phase study, using a free software package.
A case study is an in-depth and rigorous empirical investigation of a particular
phenomenon in wh... more A case study is an in-depth and rigorous empirical investigation of a particular phenomenon in which one identified case is studied within its context. Case study research as a deliberate research methodology can be traced back to 19th and 20th century developments in many different scientific disciplines, including medicine, psychology, sociology, and anthropology. Partly due to their roots in these diverse disciplines, there are many types of case studies, but case studies also vary considerably in the kind of research questions that are addressed within disciplines, and in the reasons for selecting or studying the case. Although there are serious challenges to conducting sound case study research, validity can be improved by connecting closely to theory, collecting data in a systematic and replicable way, using continuous assessment or observations during an extended period of time, using multiple sources of information, such as interviews, observations, questionnaires, and documents for the purpose of triangulation, looking at multiple cases to test tentative hypotheses, and applying formal data-analytic techniques. In this article, some common pitfalls in conducting case study research are described and references to good practice are given.
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Papers by Patrick Onghena
phenomenon in which one identified case is studied within its context. Case study research as a
deliberate research methodology can be traced back to 19th and 20th century developments in
many different scientific disciplines, including medicine, psychology, sociology, and
anthropology. Partly due to their roots in these diverse disciplines, there are many types of case
studies, but case studies also vary considerably in the kind of research questions that are
addressed within disciplines, and in the reasons for selecting or studying the case. Although
there are serious challenges to conducting sound case study research, validity can be improved
by connecting closely to theory, collecting data in a systematic and replicable way, using
continuous assessment or observations during an extended period of time, using multiple
sources of information, such as interviews, observations, questionnaires, and documents for the
purpose of triangulation, looking at multiple cases to test tentative hypotheses, and applying
formal data-analytic techniques. In this article, some common pitfalls in conducting case study
research are described and references to good practice are given.