SPSS Complex Samples

Cálculo correcto y simple de estadísticas para
muestreos complejos

IBM SPSS Complex Samples ayuda a realizar inferencias con estadísticas más válidas gracias a la incorporación del diseño de la muestra en el análisis de encuesta.

IBM SPSS Complex Samples proporciona las herramientas y estadísticas de planificación especializada necesarias para trabajar con diseños de muestras complejas, como muestreo estratificado, en clúster o en varias etapas.

• Este módulo de IBM SPSS Statistics resulta imprescindible para los investigadores de encuestas y de mercado, los investigadores de la opinión pública o los científicos sociales que quieran extraer conclusiones más precisas a partir de la metodología de encuestas de muestra. Puede trabajar de forma más precisa con resultados numéricos y categóricos en diseños de muestra complejos mediante el uso de dos algoritmos para el análisis y la predicción. Además, puede utilizar las técnicas de este modelo para prever el tiempo en que se producirá un suceso.

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• Stratified sampling - Increase the precision of your sample or ensure a representative sample from key groups by choosing to sample within subgroups of the survey population.

• Clustered sampling - Select clusters, which are groups of sampling units, for your survey. Clustering often helps makes surveys more cost-effective.

• Multistage sampling - Select an initial or first-stage sample based on groups of elements in your population; then create a second-stage sample by drawing a sub-sample from each selected unit in the first-stage sample. By repeating this option, you can select a higher-stage sample.

• IBM SPSS Complex Samples Plan (CSPLAN) – Use this procedure to specify the sampling frame to create a complex sample design or analysis specification used by companion procedures in IBM SPSS Complex Samples.

• Sampling Plan Wizard – If you are creating your own samples, use the Sampling Plan Wizard to define the scheme and draw the sample.

• Analysis Preparation Wizard – If you're using public-use datasets that already have samples, use the Analysis Plan Wizard to specify how the samples were defined and how standard errors should be estimated.

• Plan files – Once you have created plan files, you can save them and treat them as templates. This allows you to save all the decisions you made when creating the plan. This saves time and improves accuracy for yourself and others who may want to plug your plans into the data to replicate results or pick up where you left off.

• Control the scope of execution and specify a seed value with the CRITERIA subcommand

• Control whether or not user-missing values of classification (stratification and clustering) variables are treated as valid variables with the CLASSMISSING subcommand

• Specify general options concerning input and output files with the DATA subcommand

• Write sampled units to an external file using an option to keep/drop specified variables

• Automatically save first-stage joint inclusion probabilities to an external file when the plan specifies a probability proportionate to size (PPS) without replacement (WR) sampling method

• Opt to generate text files containing a rule that describes characteristics of selected units

• IBM SPSS Complex Samples Descriptives (CSDESCRIPTIVES) – Estimates means, sums and ratios, and computes standard errors, design effects, confidence intervals hypothesis tests for samples drawn by complex methods.

• Complex Sample Tabulate (CSTABULATE) – Displays one-way frequency tables or two-way crosstabulations and associated standard errors, design effects, confidence intervals and hypothesis tests for samples drawn by complex sampling methods.

• IBM SPSS Complex Samples General Linear Models (CSGLM) – Enables you to build linear regression, analysis of variance (ANOVA), and analysis of covariance (ANCOVA) models for samples drawn by complex sampling methods.

• IBM SPSS Complex Samples Logistic Regression (CSLOGISTIC) – Performs binary logistic regression analysis, as well as multiple logistic regression (MLR) analysis, for samples drawn by complex sampling methods.

• IBM SPSS Complex Samples Cox Regression (CSCOXREG) – Applies Cox proportional hazards regression to analysis of survival times; that is, the length of time before the occurrence of an event for samples drawn by complex sampling methods.