Analyze statistical data and interpret survey results from complex samples

 

The Complex Samples Module allows you to buildsample designs, by providingstatistical estimatescorrect for datasamplescomplex, increasing theprecisionand therepresentativenessof the sample. 

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It can be used in the context of:

• Healthcare research, to analyze large datasets, for example to disseminate information on the state of public health, national or world nutrition or on the diffusion of alcohol use or on the incidence of road accidents as a cause of injuries arriving in hospital

• social Sciences, for example for public polls or to group certain attitudes on political issues

• Market surveysfor customer satisfaction data analysis

 

Statistics Complex Samples provides advanced statistics and planning tools for designing complex sampling plans, so you:

• To integratesampling designs in survey analysis for more accurate results.

• Keepsurvey planning parameters for future use to speed up analyzes and increase efficiency.

• Managecomplex survey data for detailed and in-depth analysis.

• Usean intuitive interface and wizards useful for analyzing and interpreting the results of the surveys.

 

Integrate sampling designs into survey analysis

 

• Increase sample precision or obtain representative sample from the starting population.

• Select clusters to carry out cheaper surveys

 

Store survey planning parameters for future use

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• Save complex sampling plans as a template for use on a new population.

• Share and save sample designs for later retrieval.

 

Manage complex survey data

 

• View frequency tables or cross tabulations and associated standard errors, design effects, confidence intervals, and hypothesis tests.

• Develop linear regression models, analysis of variance (ANOVA) and analysis of covariance (ANCOVA).

• Estimate means, sums, and percentages, calculate standard errors, design effect confidence intervals, and hypothesis tests for samples designed using complex sample models.

• Perform binary logistic regression analysis and multiple logistic regression (MLR) analysis.

• Apply the Cox proportional hazards regression to the survival analysis.

 

Use an intuitive interface and wizards

 

• Use the Analysis Preparation Wizard (APW) to specify how samples are defined and standard errors are estimated.

• Use the Sampling Plan Wizard to define the pattern and design the sample, when creating custom templates.

• Use the Statistics Complex Samples Selection (CSSELECT) procedure to select complex samples based on probabilities, reducing the risk of misrepresentation of a subset.