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STRATA
Household strata for variance estimation

Description

STRATA is designed for use with CLUSTER in Taylor series linear approximation for correction of complex sample design characteristics.

While appropriate use of the sampling weights PERWT and HHWT allow users to produce correct point estimates (such as means and proportions), many researchers believe that additional statistical techniques are also necessary to produce correct standard errors and statistical tests that account for complex sample design.

For further information on why and how to use STRATA and CLUSTER, see Analysis and Variance Estimation with the IPUMS . For more details on the mathematics behind this method, see Issues Concerning the Calculation of Standard Errors Using IPUMS Data Products .

Codes

STRATA is a 12-digit numeric variable designed for use with CLUSTER in Taylor series linear approximation for correction of complex sample design characteristics. While appropriate use of the sampling weights PERWT and HHWT allow users to produce correct point estimates (such as means and proportions), many researchers believe that additional statistical techniques are also necessary to produce correct standard errors and statistical tests that account for complex sample design. STRATA specific variable codes for missing, edited, or unidentified observations, observations not applicable (N/A), observations not in universe (NIU), top and bottom value coding, etc. are provided below if applicable by Census year (and data sample if specified).

User Note: For further information on why and how to use STRATA and CLUSTER, see Analysis and Variance Estimation with the IPUMS. For more details on the mathematics behind this method, see Issues Concerning the Calculation of Standard Errors Using IPUMS Data Products.

STRATA Specific Variable Codes

Comparability

CLUSTER and STRATA are currently available for samples from 1850 to the present.

For samples from 1850-1930, pseudo strata were created based on microfilm page ranges, which serve as a proxy for geographic stratification. For 1940-1950, strata were created from enumeration districts (ENUMDIST). For more information on the creation of strata, see "Drawing Statistical Inferences from Historical Census Data," in the August 2009 issue of Demography.

For the 1960-2000 samples, strata were created based on the stratification criteria used to select PUMS samples such as household size, age, race, ethnicity, tenure, group quarters membership, and vacancy status. For more information on the creation of strata, see this Constructing strata in the IPUMS samples.

For the American Community Survey (ACS) samples strata were created from the lowest level of geography available in each sample. For the 2000-2004 samples, each state forms a stratum. In the 2005 onward ACS samples, strata are defined as unique Public Use Micro-data Areas (PUMA).

Universe

  • All households and group quarters. Not available for Puerto Rico, Alaska, Hawaii, or the American Indian schedules.

Availability

United States
  • 2017: All samples
  • 2016: All samples
  • 2015: All samples
  • 2014: All samples
  • 2013: All samples
  • 2012: All samples
  • 2011: All samples
  • 2010: All samples
  • 2009: All samples
  • 2008: All samples
  • 2007: All samples
  • 2006: All samples
  • 2005: All samples
  • 2004: All samples
  • 2003: All samples
  • 2002: All samples
  • 2001: All samples
  • 2000: All samples
  • 1990: All samples
  • 1980: All samples
  • 1970: All samples
  • 1960: 1%
  • 1950: All samples
  • 1940: 1%
  • 1930: 1%; 5%
  • 1920: 1%
  • 1910: 1%; 1.4% ovrsmp
  • 1900: 5%; 1%; 1.2% ovrsmp
  • 1880: 1%
  • 1870: All samples
  • 1860: All samples
  • 1850: 1%
Puerto Rico
  • 2017: --
  • 2016: --
  • 2015: --
  • 2014: --
  • 2013: --
  • 2012: --
  • 2011: --
  • 2010: --
  • 2009: --
  • 2008: --
  • 2007: --
  • 2006: --
  • 2005: --
  • 2000: --
  • 1990: --
  • 1980: --
  • 1970: --
  • 1930: --
  • 1920: --
  • 1910: --

Flags

This variable has no flags.

Editing Procedure

There is no editing procedure available for this variable.