Methodology series module 3: Cross-sectional studies
Cross-sectional study design is a type of observational study design. In a cross-sectional study, the investigator measures the outcome and the exposures in the study participants at the same time. Unlike in case–control studies (participants selected based on the outcome status) or cohort studies (...
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doaj-5529ebb01a954c9eb89179ff3df925402020-11-25T00:22:23ZengWolters Kluwer Medknow PublicationsIndian Journal of Dermatology0019-51541998-36112016-01-0161326126410.4103/0019-5154.182410Methodology series module 3: Cross-sectional studiesManinder Singh SetiaCross-sectional study design is a type of observational study design. In a cross-sectional study, the investigator measures the outcome and the exposures in the study participants at the same time. Unlike in case–control studies (participants selected based on the outcome status) or cohort studies (participants selected based on the exposure status), the participants in a cross-sectional study are just selected based on the inclusion and exclusion criteria set for the study. Once the participants have been selected for the study, the investigator follows the study to assess the exposure and the outcomes. Cross-sectional designs are used for population-based surveys and to assess the prevalence of diseases in clinic-based samples. These studies can usually be conducted relatively faster and are inexpensive. They may be conducted either before planning a cohort study or a baseline in a cohort study. These types of designs will give us information about the prevalence of outcomes or exposures; this information will be useful for designing the cohort study. However, since this is a 1-time measurement of exposure and outcome, it is difficult to derive causal relationships from cross-sectional analysis. We can estimate the prevalence of disease in cross-sectional studies. Furthermore, we will also be able to estimate the odds ratios to study the association between exposure and the outcomes in this design.http://www.e-ijd.org/article.asp?issn=0019-5154;year=2016;volume=61;issue=3;spage=261;epage=264;aulast=SetiaCross-sectional studiesdesignlimitationsstrengths |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Maninder Singh Setia |
spellingShingle |
Maninder Singh Setia Methodology series module 3: Cross-sectional studies Indian Journal of Dermatology Cross-sectional studies design limitations strengths |
author_facet |
Maninder Singh Setia |
author_sort |
Maninder Singh Setia |
title |
Methodology series module 3: Cross-sectional studies |
title_short |
Methodology series module 3: Cross-sectional studies |
title_full |
Methodology series module 3: Cross-sectional studies |
title_fullStr |
Methodology series module 3: Cross-sectional studies |
title_full_unstemmed |
Methodology series module 3: Cross-sectional studies |
title_sort |
methodology series module 3: cross-sectional studies |
publisher |
Wolters Kluwer Medknow Publications |
series |
Indian Journal of Dermatology |
issn |
0019-5154 1998-3611 |
publishDate |
2016-01-01 |
description |
Cross-sectional study design is a type of observational study design. In a cross-sectional study, the investigator measures the outcome and the exposures in the study participants at the same time. Unlike in case–control studies (participants selected based on the outcome status) or cohort studies (participants selected based on the exposure status), the participants in a cross-sectional study are just selected based on the inclusion and exclusion criteria set for the study. Once the participants have been selected for the study, the investigator follows the study to assess the exposure and the outcomes. Cross-sectional designs are used for population-based surveys and to assess the prevalence of diseases in clinic-based samples. These studies can usually be conducted relatively faster and are inexpensive. They may be conducted either before planning a cohort study or a baseline in a cohort study. These types of designs will give us information about the prevalence of outcomes or exposures; this information will be useful for designing the cohort study. However, since this is a 1-time measurement of exposure and outcome, it is difficult to derive causal relationships from cross-sectional analysis. We can estimate the prevalence of disease in cross-sectional studies. Furthermore, we will also be able to estimate the odds ratios to study the association between exposure and the outcomes in this design. |
topic |
Cross-sectional studies design limitations strengths |
url |
http://www.e-ijd.org/article.asp?issn=0019-5154;year=2016;volume=61;issue=3;spage=261;epage=264;aulast=Setia |
work_keys_str_mv |
AT manindersinghsetia methodologyseriesmodule3crosssectionalstudies |
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1725360148889731072 |