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Calculate Rates (Spatial Statistics Tools)

Summary

Calculates crude or smoothed rates. The global empirical Bayes rate method smooths the rates toward a global reference rate. The local empirical Bayes, locally weighted average, and locally weighted median rate methods use local neighbors to spatially smooth rates.

Learn more about how Calculate Rates works

Usage

  • If the Input Table or Features parameter value is a table, the options for the Rate Method parameter will be limited to Crude Rate and Global Empirical Bayes. The Local Empirical Bayes, Locally Weighted Average, and Locally Weighted Median options are only valid for spatial data.

  • The tool provides several Neighborhood Type parameter options. However, to customize the neighborhoods further, use Neighborhood Explorer to configure the neighborhoods and to export a .swm file. Use the .swm file as the Spatial Weights Matrix parameter value.

  • If the rate values are small, they may be difficult to interpret. Use the Rate Multiplier parameter to scale the rates or to report the rates per specific unit of population. For example, if the Rate Multiplier value is 10,000, the rates will be reported as a number per 10,000 people.

  • If a spatial smoothing rate method is selected, each focal feature will be included in its own neighborhood. For example, if the Neighborhood Type parameter value is K Nearest Neighbors and the Number of Neighbors parameter value is 7, each feature will have a neighborhood with 8 features. The entire neighborhood is used to calculate the rate of a focal feature.

  • If the Rate Method parameter is set to Local Empirical Bayes, Locally Weighted Average, or Locally Weighted Median, the output will include a Number of Non-Null Neighbors field. This field contains the number of neighbors, including the focal feature, that did not have a negative or null value in the Population Field and Count Field parameter values.

  • Features with a value of 0 in the Population Field value will receive a null crude rate value.

  • If the Rate Method parameter is set to Locally Weighted Average or Locally Weighted Median, the output will include a Fill Missing Value field. This field indicates whether a rate was imputed for a feature with a negative or null Count Field or Population Field value.

Parameters

Label Explanation Data type

Input Table or Features

The table or features containing count fields and population fields to calculate rates.

Table View

Rate Fields

The count and population fields that will be used to calculate rates.

Value table columns:

  • Count Field—The count fields.

  • Population Field—The population field.

Value Table

Append Fields to Input

(Optional)

Specifies whether fields will be appended to the input dataset or saved to an output table or feature class.

  • Checked—Fields will be appended to the input features. This modifies the input data.

  • Unchecked—An output table or feature class containing the fields will be created. This is the default.

Boolean

Output Table or Features

(Optional)

The output table or feature class containing the rates and additional fields to help evaluate the rates.

Feature Class; Table

Rate Method

(Optional)

Specifies the method that will be used to calculate rates.

  • Crude Rate—The rates will be calculated by dividing the count field values by the population field values. This is the default.

  • Global Empirical Bayes—The rates will be the weighted average of the crude rate and the global average rate. The weight will depend on the feature's population size.

  • Local Empirical Bayes—The rates will be the weighted average of the focal feature's crude rate and the weighted average rate of its neighborhood.

  • Locally Weighted Average—The rates will be the spatially weighted average rate of each feature and its neighborhood.

  • Locally Weighted Median—The rates will be the spatially weighted median rate of each feature and its neighborhood.

String

Probability Distribution

Specifies the probability distribution of the count field.

  • Poisson—The count field is assumed to follow a Poisson distribution. This is the default.

  • Binomial—The count field is assumed to follow a binomial distribution.

String

Neighborhood Type

(Optional)

Specifies the method that will be used to identify the neighbors of each feature.

  • Distance Band—A threshold distance is applied to identify neighbors. Every feature that is within the threshold distance of a focal feature is considered a neighbor. If the input contains point or line features, this is the default. Distance Band

  • Contiguity Edges Only—Polygon features that share an edge or overlap a feature become neighbors of that feature. Contiguity Edges Only

  • Contiguity Edges Corners—Features that overlap, share an edge, or share a vertex with a feature are neighbors of that feature. If the input contains polygon features, this is the default. Contiguity Edges Corners

  • K Nearest Neighbors—The same number of neighbors, k, is assigned to every feature. The k nearest features to a feature become its neighbors. K Nearest Neighbors

  • Delaunay Triangulation—A nonoverlapping mesh of triangles is created from feature centroids. Each feature is a triangle node and nodes that share edges are considered neighbors. Delaunay Triangulation

  • Get Spatial Weights from File—The spatial relationships between features is defined in a spatial weights matrix (.swm) file.

String

Distance Band

(Optional)

The distance from each feature that will be used to search for neighbors. All features within this distance will be included as neighbors.

Linear Unit

Number of Neighbors

(Optional)

The number of neighbors that will be included in a feature's neighborhood.

Long

Spatial Weights Matrix

(Optional)

The path and file name of the spatial weights matrix file that defines the spatial relationships among features.

File

Local Weighting Scheme

(Optional)

Specifies the weighting scheme that will be applied to neighbors when calculating local statistics.

  • Unweighted—Neighbors will not be weighted. This is the default.

  • Bisquare—Neighbors will be weighted using a bisquare kernel scheme.

  • Gaussian—Neighbors will be weighted using a Gaussian kernel scheme.

String

Kernel Bandwidth

(Optional)

The bandwidth of the bisquare or Gaussian local weighting schemes. If no value is provided, one will be estimated during processing and included as a geoprocessing message.

Linear Unit

Rate Multiplier

A constant value that will be multiplied by the rates. This parameter can be used to scale the rates or to report the rates per specific unit of population. For example, when the value is set to 10,000, the rates will be reported as a number per 10,000 people.

Long

Derived output

Label Explanation Data type

Updated Input Table

The updated input table.

Table View

Output Layer Group

If a feature class is specified for the Input Table or Features parameter, a group layer is output with a layer for each rate specified in the Rate Fields parameter.

Group Layer

Environments

Output Coordinate System

Licensing information

  • Basic: Yes
  • Standard: Yes
  • Advanced: Yes