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Are your C4 data reflective of the families you serve?

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Percent of families participating in Part C who report that early intervention ... all Part C families in program more than 1 year. ... – PowerPoint PPT presentation

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Title: Are your C4 data reflective of the families you serve?


1
  • Are your C4 data reflective of the families you
    serve?

Joy Markowitz, Director Jean Dauphinee, TA
Specialist
Measuring Child and Family Outcomes Conference,
August 28, 2008
2
Purpose of Collecting C4 data
  • To figure out how to serve our families better
    specifically related to Indicator C4
  • Percent of families participating in Part C who
    report that early intervention services have
    helped the family
  • A Know their rights
  • B. Effectively communicate their children's
  • needs and
  • C. Help their children develop and learn.

3
Why do we care who responds to our surveys?
  • We dont want to invest time and money in
  • improvement activities if data do not reflect the
  • opinions and/or experiences of the
  • families/children we serve.
  • This is an issue if you collect data from all
  • families (census) or a sample of families
  • because not all families who receive a survey
  • respond.

4
Population
  • Population may be defined by the state and could
    be (for example)
  • all Part C families
  • all Part C families exiting in a given year, or
  • all Part C families in program more than 1 year.

5
Other terms used
  • Population
  • Target group
  • Target population
  • Respondents
  • Response Pool
  • Respondent Pool
  • Respondent Group

6
Nonresponse Bias
  • Representativeness is a word we have been
  • using. Its not a statistical term.
  • Correct term nonresponse bias.
  • Meaning Are the families who did not
  • respond different from the families that did?

7
What is a Sample?
  • A sample is a subset of the population that
  • you define. However, this sample must
  • be derived using an approved sampling
  • plan.
  • OSEP collaborates with DAC to review and
  • approve submitted sampling plans.

8
Questions about Response Rates
  • What is high enough?
  • How do you determine if your respondents
  • are reflective of the population you
  • defined?
  • Whether using census or sampling, your
  • return or response rate is unlikely to be as
  • high as you want it to be therefore, you must
  • address nonresponse bias.

9
Example 1
Families served in 2006-2007 (n100)
  • Survey respondents
  • Black 24
  • White 44
  • AI/AN 2
  • Total 70
  • Families served
  • Black 30
  • White 50
  • AI/AN 20
  • Total 100

Do these data reflect the population?
10
Example 2
Families exiting in 2006-2007 (n100)
  • Survey respondents
  • English 65
  • Other language 5
  • Total 70
  • Families served
  • English 75
  • Other language 25
  • Total 100

Do these data reflect the population?
11
Example 3
Families served in programs for at least one year
(n100)
  • Families served by agencies
  • Agency 1 100
  • Agency 2 100
  • Agency 3 100
  • Agency 4 100
  • Total 400
  • Survey respondents
  • Agency 1 49
  • Agency 2 63
  • Agency 3 66
  • Agency 4 21
  • Total 199

Do these data reflect the population?
12
State Data Collection Methods/Strategies
  • Analysis strategies
  • Frequencies and
  • percentages
  • Weighting
  • Sampling among
  • respondents
  • Methods
  • Census (n41 states)
  • Sample (n 15 states)
  • oversampling populations that are known to be
    hard to reach.

13
Summary of C4 Findings(Based on analysis of 54
state 2006-2007 APRs)
  • 67 (n 36 states) reported nonresponse bias, 26
    (n14 states) did not.
  • Among the 67 who reported nonresponse bias, most
    reported by one variable (e.g. race/ethnicity,
    region, gender, or childs age)

14
Summary of C4 Findings(Based on analysis of 54
state 2006-2007 APRs) cont.
  • Most states measured nonresponse bias by
  • Race/ethnicity or
  • Race/ethnicity and other factors such as
  • length of time in program,
  • region of the state,
  • childs age, or
  • gender.


15
From SPP/APR Instruction Sheet
  • States are allowed to use sampling when so
    indicated on the Part C Indicator Measurement
    Table. When sampling is used, a description of
    the sampling methodology outlining how the design
    will yield valid and reliable estimates must be
    submitted to OSEP. The description must describe
    the
  • (a) sampling procedures followed (e.g.,
    random/stratified, forms validation) and
  • (b) the similarity or differences of the sample
    to the population of children with disabilities
    in the early intervention program (e.g., how all
    aspects of the population such as disability
    category, race, age, gender, etc. will be
    represented).

16
From SPP/APR Instruction Sheet (cont.)
  • The description must also include how the Lead
    Agency addresses any problems with
  • (1) response rates
  • (2) missing data and
  • (3) selection bias.
  • Samples from EIS programs must be representative
    of each of the EIS programs sampled, considering
    such variables as eligibility definition
    (diagnosed condition or developmental delay),
    age, race, and gender.

17
From SPP/APR Instruction Sheet (cont.)
  • In reporting on the performance of small EIS
    programs, the Lead Agency shall not report to the
    public or the Secretary any information on
    performance that would result in the disclosure
    of personally identifiable information about
    individual children or where the available data
    is insufficient to yield statistically reliable
    information, i.e., numbers are too small.
  • Source Part C State Performance Plan (SPP) and
    Annual Performance Report (APR) Instruction Sheet
    dated 10/19/2007.

18
Examples from States
  • How have states tackled these issues?
  • State representatives
  • Wendy Whipple, NV
  • Sue Campbell and Rosanne Griff-Cabelli, DE
  • Alice Ridgeway, CT

19
Questions?
  • What questions are you getting from OSEP that you
    need help to answer?
  • What guidance do you need from OSEP?
  • What are realistic expectations of states for
    reporting nonresponse bias?
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