The O*NET Data Collection Program is
an ongoing effort to collect and maintain current information on
the detailed characteristics of occupations and skills for more
than 900 occupations. The resulting database provides the most
comprehensive standardized source of occupational and skills
information in the nation. O*NET information is used by a wide
range of audiences, including individuals making career decisions,
public agencies and schools providing career exploration services
or education and training programs, and businesses making staffing
and training decisions. The O*NET system provides a common
language, framework and database to meet the administrative needs
of various federal programs, including workforce investment and
training programs supported by funding from the Departments of
Labor, Education, and Health and Human Services.
PL:
Pub.L. 113 - 128 308 Name of Law: Workforce Innovation and
Opportunity Act
US Code:
29 USC 3101-3255 Name of Law: Workforce Innovation and
Opportunity Act
US Code: 29
USC 491-492 Name of Law: Wagner-Peyser Act
The projected total annual
burden hours for July 2015–June 2018 range from 13,918 to 15,375.
The average annual burden is 14,537 hours, compared with an average
annual burden of 13,671 hours requested for the previous 3-year
period (2012–2015). The total burden hours for the July 2015–June
2018 period, 43,610, reflect a slight increase in burden compared
with the 2012–2015 period, for which a total 41,011 hours were
requested (U.S. Department of Labor, Employment & Training
Administration, 2012). The small increase in burden corresponds to
an increase in the number of establishment sampling units that are
contacted each year, an estimated 49,667 for the July 2015–June
2018 period compared with 43,500 for the June 2012–May 2015 period
in the April 10, 2012, OMB Supporting Statement. The slight
increase in the number of sampled establishments is attributable to
changes in the schedule for fielding cases (occupations), which is
impacted by eligibility rates and other sampling characteristics of
the specific occupations being studied. The annual costs have
increased since 2012–2015, primarily because of inflation in the
benefits portion of employee compensation and also because of the
increase in the number of sampling units being contacted per year
relative to the 2012–2015 period. A few minor questionnaire
revisions have been implemented since 2012. In addition, several
minor questionnaire revisions for the Knowledge Questionnaire and
the Background Questionnaire are pending in this submission. All of
these revisions are described in detail in Appendix A. These minor
revisions do not represent an increase in respondent burden. As
with the burden hours, the slight decrease in total cost burden
across the 2 year period July 2016–June 2018 relative to the July
2015–June 2016 period results from initiation of data collection
for most occupations during July 2015–June 2016, which causes many
of these occupations to complete data collection during the final 2
years. Weighting and Estimation Estimates generated from O*NET
survey data are computed with sampling weights that compensate for
the unequal probabilities of selecting establishments, occupations
within establishments, and employees within each selected
occupation. In addition, these base weights are adjusted to further
compensate for multiple subwaves of sampling, sample adjustment,
population under- and overcoverage caused by frame imperfections,
and nonresponse at both the establishment and the employee levels.
These weight adjustments can lead to weights that are very large or
very small compared with the weights for other sample units. Such
weight variability may increase the standard error estimates. When
the variation in the weights is large, it is desirable to trim the
weights to reduce the variation. For the O*NET estimates, the
weighting process involves a weight trimming procedure in which
extremely large or small weights are truncated to fall within a
specified range. Although trimming weights can introduce bias in
the estimates, the variance reduction it achieves usually offsets
the potential bias, resulting in estimates with smaller net mean
squared errors.
On behalf of this Federal agency, I certify that
the collection of information encompassed by this request complies
with 5 CFR 1320.9 and the related provisions of 5 CFR
1320.8(b)(3).
The following is a summary of the topics, regarding
the proposed collection of information, that the certification
covers:
(i) Why the information is being collected;
(ii) Use of information;
(iii) Burden estimate;
(iv) Nature of response (voluntary, required for a
benefit, or mandatory);
(v) Nature and extent of confidentiality; and
(vi) Need to display currently valid OMB control
number;
If you are unable to certify compliance with any of
these provisions, identify the item by leaving the box unchecked
and explain the reason in the Supporting Statement.
List_of_Changes.pdf
ONET 1205-0421 PartB-4-8-2015.docx
O*NET/Private Sector Establishments