<i>%svy_freqs</i>: A Generic SAS Macro for Creating Publication-Quality Three-Way Cross-Tabulations

AbstractIntroductionIn epidemiological studies, cross-tabulations are a simple but important tool for understanding the distribution of socio-demographic characteristics among study participants. They become more useful when comparisons are presented using a by-group variable such as key demographic characteristic or an outcome status; for instance, sex or the presence or absence of a disease status. Most available statistical analysis software can easily perform cross-tabulations, however, output from these must be processed further to make it readily available for review and use in a publication. In addition, performing three-way cross-tabulations of complex survey data such as those required to show the distribution of disease prevalence across multiple factors and a by-group variable is not easily implemented directly using available standard procedures of commonly used statistical software.MethodsWe developed a generic SAS macro, %svy_freqs, to create quality publication-ready tables from cross-tabulations between a factor and a by-group variable given a third variable using survey or non-survey data. The SAS macro also performs classical two-way cross-tabulations and refines output into publication-quality tables. It provides extra features not available in existing procedures such as ability to incorporate parameters for survey design and replication-based variance estimation methods, performing validation checks for input parameters, transparently formatting character variable values into numeric ones and allowing for generalizability.ResultsWe demonstrate the application of the SAS macro in the analysis of data from the 2013-2014 National Health and Nutrition Examination Survey (NHANES), a complex survey designed to assess the health and nutritional status of adults and children in the United States (U.S.).ConclusionThe SAS code use to develop the macro is simple yet comprehensive, easy to follow, straightforward for the end user and simple for a SAS programmer to extend. The SAS macro has shown to shorten turn-around time for statistical analysis, eliminate errors when preparing output, and support reproducible research.

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Small Computer System for Micrograph Analysis

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100097879 ◽

1981 ◽

Vol 39 ◽

pp. 270-271

Author(s):

J. F. Hainfeld ◽

J. S. Wall

Keyword(s):

Large Range ◽

Small Computer ◽

Black And White ◽

Contour Maps ◽

Points Of Interest ◽

Computer Aided Analysis ◽

Specialized Hardware ◽

Additional Memory ◽

Selection Of ◽

Publication Quality

Cost reduction and availability of specialized hardware for image processing have made it reasonable to purchase a stand-alone interactive work station for computer aided analysis of micrographs. Some features of such a system are: 1) Ease of selection of points of interest on the micrograph. A cursor can be quickly positioned and coordinates entered with a switch. 2) The image can be nondestructively zoomed to a higher magnification for closer examination and roaming (panning) can be done around the picture. 3) Contrast and brightness of the picture can be varied over a very large range by changing the display look-up tables. 4) Marking items of interest can be done by drawing circles, vectors or alphanumerics on an additional memory plane so that the picture data remains intact. 5) Color pictures can easily be produced. Since the human eye can detect many more colors than gray levels, often a color encoded micrograph reveals many features not readily apparent with a black and white display. Colors can be used to construct contour maps of objects of interest. 6) Publication quality prints can easily be produced by taking pictures with a standard camera of the T.V. monitor screen.

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The role of microRNAs in gliomas – Therapeutic implications

Current Molecular Pharmacology ◽

10.2174/1874467213666200730115837 ◽

2020 ◽

Vol 13 ◽

Author(s):

Theodora Katsila ◽

Dimitrios Kardamakis

Keyword(s):

Complex Disease ◽

Malignant Gliomas ◽

Kappa Statistic ◽

Individual Variability ◽

Response To Treatment ◽

Disease Phenotype ◽

Therapeutic Implications ◽

Non Invasive ◽

Gene Environment ◽

Sas Macro

Background: Malignant gliomas constitute a complex disease phenotype that demands optimum decisionmaking. Despite being the most common type of primary brain tumors, gliomas are highly heterogeneous when their pathophysiology and response to treatment are considered. Such inter-individual variability also renders differential and early diagnosis extremely difficult. Recent evidence highlight that the gene-environment interplay becomes of fundamental importance in oncogenesis and progression of gliomas. Objective: To unmask key features of the gliomas disease phenotype and map the inter-individual variability of patients, we explore genotype-to-phenotype associations. Emphasis is put on microRNAs as they regulate gene expression, have been implicated in the pathogenesis of gliomas and may serve as theranostics, empowering non-invasive strategies (circulating free or in exosomes). Method: We mined text and omic datasets (as of 2019) and conducted a mixed-method content analysis. A novel framework was developed to meet the aims of our analysis, interrogating data in terms of content and context. We relied on literature data from PubMed/Medline and Scopus, as they are considered the largest abstract and citation databases of peer-reviewed literature. To avoid selection biases, both publicly available and private texts have been assessed. Both percent agreement and Cohen's kappa statistic have been calculated to avoid biases by SAS macro MAGREE with multicategorical ratings. Results: Gliomas serve as a paradigm for multifaceted datasets, despite data sparsity and scarcity. miRNAs and miRNAbased therapeutics are ready for prime time. Exosomal miRNAs empower non-invasive strategies, surpassing circulating free miRNAs, when accuracy and precision are considered. Conclusion: miRNAs holds promise as theranostics.

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