SUPPORTING STATEMENT Part B Dec 2.revised

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National Occupational Safety and Health Professional Workforce Assessment: Employer and Education Provider Survey Data Collection

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SUPPORTING STATEMENT—Part B: Collections of Information Employing Statistical Methods







National Occupational Safety and Health Professional Workforce Assessment: Employer and Education Provider Survey Data Collection






















M. Chris Langub, PhD

Scientific Review Officer
Office of Extramural Programs
National Institute for Occupational Safety and Health
email: [email protected]
404-498-2543 (Office)

404-498-2571 (Fax)




December 2010

Table of Contents

B. Collections of Information Employing Statistical Methods 1


1.0 Respondent Universe and Sampling Methods 1


1.a Educational Providers 1

1.b Employers 1


  1. Procedures for Collection of Information 17


  1. Methods to Maximize Response Rates and Deal with Non-response 17

3.a Methods to Maximize Response Rates 17

3.b Methods to Deal with Non-Response 18


  1. Tests of Procedures 19


  1. Individuals Consulted on Statistical Aspects and 20

Individuals Collecting or Analyzing the Data



B. Collections of Information Employing Statistical Methods


1.0 Respondent Universe and Sampling Methods

The Occupational Safety and Health (OS&H) professions about which data will be collected include safety, industrial hygiene, occupational medicine, occupational health nursing, health physics, ergonomics, occupational epidemiology, occupational injury prevention, and occupational health psychology. Two separate groups are being surveyed in this study, one is the providers of OS&H education and training and the other is the potential employers of OS&H professionals. We will discuss each group separately.


1.a Educational Providers

The universe for this portion of the study is college and university programs that provide at least bachelor’s degrees in some OS&H profession. This includes approximately 400 programs. We are compiling lists of OS&H education and training programs from professional associations, professional certification bodies, from our Task Force contacts, and from the list of NIOSH funded programs.  We will merge this information into a single listing of OS&H provider programs, which will then constitute the provider population for this survey. To be eligible for inclusion, a “program” must offer at least a Bachelor’s degree in one or more of the nine OS&H categories of interest to NIOSH for this survey. Based on the information currently available to us, we believe we cover nearly all of the OS&H programs in colleges and universities, and so we propose to include all of these programs in our survey. We expect this to be about 400 providers and expect approximately 180 to participate.


1.b Employers

The universe for this portion of the study is all employers of OS&H professionals. NIOSH’s objective for this effort is to provide statistically defensible estimates for each specialty. The following paragraphs describe our sample design.



The sample design will generate a national probability sample of employers of Occupational Safety and Health (OS&H) professionals. The survey will cover industries with the largest concentrations of OS&H professionals while including 75 percent of these professionals. The survey will use a stratified random sample design. The larger employers and employers in industries where OS&H professionals are concentrated will be oversampled. The target sample size is 400 completed interviews. This section describes the sample design. It includes a description of the respondent universe and sampling frame, sample size determination, stratification and sample size allocation, and expected precision of the estimates.




1.b.1 Respondent universe and sampling frame


The target population of employers of OS&H professionals presents a rare population problem relative to the general employer population. If a simple random sample of employers were selected, an enormous screener sample size would be needed to identify the employers of OS&H professionals. To avoid this inefficiency, we plan to use a stratified design that identifies the industries where OS&H professionals are concentrated, and oversample the employers in those industries to reduce the screening. Other industries where the number of OS&H workers is small can be excluded without increasing the overall under coverage substantially or causing noticeable bias in the estimates. We used the Occupational Employment Statistics (OES) survey data from the Bureau of Labor Statistics (BLS) to identify the industries where employment of OS&H professionals is concentrated.



The OES survey provides employment and wage statistics for detailed occupations, including Occupational Health and Safety (OHS) specialists. Estimates are provided for detailed industries, e.g., by 4-digit NAICS.


The BLS’s OHS specialists occupation (OCC code of: 29-9011) includes four of the six largest specialties of interest for this survey: industrial hygienists, safety professionals, ergonomists, and health physicists. Membership numbers for the American College Occupational of Occupational and Environmental Medicine (ACOEM) and the American Association of Occupational Health Nurses (AAOHN) suggests there are sizable numbers of occupational physicians and occupational health nurses, however, they do not have separate OCC codes in BLS. Also, the three other smaller OS&H specialties are expected to have very small numbers relative to medicine and occupational health nursing do not have separate OCC Codes. With the extensive coverage of the OHS specialists group, for this survey we have assumed that the specialties not included in this code are likely to be found in the same industries where OHS specialists are concentrated. Therefore, for our sampling plan to identify employers of the nine OS&H professional specialties of interest we have concentrated on those industries where OHS specialists are found.


Table 1 shows the 29 industries (defined by 4-digit NAICS) with the largest numbers of OHS specialists based on the 2008 OES data. As shown in Table 1, the total number of OHS specialists in the nation is 51,800 and the 29 industries, together, contain 38,840 OHS specialists, thus covering 75 percent of the total OHS specialist employment. To maximize the efficiency of this survey, we therefore have defined these 29 industries to be “in scope.”


We have determined that a cutoff of establishments of fewer than 100 employees will substantively decrease the cost of screening and increase its efficiency. Excluding smaller employers will decrease the frequency of screening closed businesses or businesses that do not employ OS&H professionals. Therefore, the sampling universe will exclude establishments with fewer than 100 employees. However, there are certain employers whose focus is on providing OS&H services, such as OS&H consultants and occupational medicine clinics that likely normally have fewer than 100 employees. For these employers we will include establishments with fewer than 100 employees.






Table 1. Industries with the largest numbers of occupational health and safety (OHS) specialists

covering 75 percent of the total OHS specialist employment







 

 

 

 


 


Percent of


 


the total

Industries by 4-digit NAICS

OHS specialist

OHS specialist

NAICS Code

Description

employment

employment


 



211100

Oil and Gas Extraction

480

0.93

212100

Coal Mining

220

0.42

212200

Metal Ore Mining

160

0.31

213100

Support Activities for Mining

770

1.49

221100

Electric Power Generation, Transmission and Distribution

940

1.81

311600

Animal Slaughtering and Processing

320

0.62

322100

Pulp, Paper, and Paperboard Mills

160

0.31

324100

Petroleum and Coal Products Manufacturing

310

0.60

325100

Basic Chemical Manufacturing

530

1.02

325200

Resin, Synthetic Rubber, and Artificial Synthetic Fibers and Filaments Manufacturing

380

0.73

325400

Pharmaceutical and Medicine Manufacturing

370

0.71

331100

Iron and Steel Mills and Ferroalloy Manufacturing

120

0.23

331300

Alumina and Aluminum Production and Processing

140

0.27

331400

Nonferrous Metal (except Aluminum) Production and Processing

180

0.35

331500

Foundries

180

0.35

336300

Motor Vehicle Parts Manufacturing

230

0.44

336400

Aerospace Product and Parts Manufacturing

670

1.29

482100

Rail Transportation

160

0.31

491100

Postal Service

410

0.79

492100

Couriers and Express Delivery Services

360

0.69

541600

Management, Scientific, and Technical Consulting Services

3370

6.51

541700

Scientific Research and Development Services

1110

2.14

551100

Management of Companies and Enterprises

1450

2.80

611300

Colleges, Universities, and Professional Schools

1650

3.19

622100

General Medical and Surgical Hospitals

3040

5.87

622300

Specialty (except Psychiatric and Substance Abuse) Hospitals

190

0.37

999100

Federal Executive Branch (OES Designation)

6820

13.17

999200

State Government (OES Designation)

7330

14.15

999300

Local Government (OES Designation)

6790

13.11


 



Subtotal

 

38,840

74.98

All remaining industries



12,960

25.02


 



Total

 

51,800

100.00





Source: 2008 OES survey, Occupational Employment and Wage Estimates, http://www.bls.gov/oes/oes_dl.htm



Sampling frame


We explored several establishment lists of potential value for developing population frames for the employer survey. The business registers maintained by Bureau of Labor Statistics (BLS) and the U.S. Bureau of Census, although desirable choices for a sampling frame, cannot be used due to confidentiality and data restrictions. We also examined the option of using the OES establishment sample list, which identifies the establishments containing an OHS specialist. This approach would have eliminated the screener costs almost completely. However, our request to BLS for access was not granted.


The Dun & Bradstreet (D&B) database, formerly known as the Dun’s market Identifiers (DMI) register maintained by Dun & Bradstreet (D&B), is the most comprehensive establishment list available for public use. The D&B database, which is updated monthly, covers all of the U.S. economy and its coverage of most industries is quite complete. The records contain the following fields: a D-U-N-S number; North American Industry Classification System (NAICS) code or Standard Industrial Classification (SIC) code; Federal Information Processing Standards (FIPS) state code; Standard Metropolitan Statistical Area (SMSA) code; number of employees at the location; total number of employees for the entire organization; status indicator, i.e., single location, headquarters, or branch; a subsidiary indicator; D-U-N-S numbers of the domestic topmost firm, headquarters, and parent (if a subsidiary); and hierarchy and DIAS codes to identify its location within the corporate structure.


The D&B database provides the option of choosing alternative organizational levels. The database includes both headquarters and branch level records. It defines a headquarters as a business establishment that has branches or divisions reporting to it, and is financially responsible for those branches or divisions. The sampling unit for this survey is the establishment. Thus, we will include both headquarters and branches as separate sampling units in the sampling frame. The headquarters record provides the total number of employees for the company, including the employees in the branches and the number of employees at the location. We will use D&B’s information on the number of employees at the location in designing the sample.



1.b.2 Sample size determination


The survey targets 400 completed interviews with employers of OS&H professionals. We estimate that we will need to sample at least 9,211 establishments (assuming that we will be able to reach at least 85% of them during the screening process).

If we assume we can successfully complete screening interviews with at least 85 % of these establishments (e.g., some will have gone out of business), we estimate that we will need to screen 7,829 establishments by telephone to identify 1,000 eligible establishments (i.e., establishments that employ one or more OS&H professionals) to participate in the survey. When we establish eligibility we will obtain or confirm mailing contact information. We expect that 40% of the 1,000 eligible establishments will complete the survey, yielding a total of 400 completed surveys.

The following is a description of the derivation of the total sample sizes stated above. Table 2 shows the sample size needed for each of the 29 in-scope industries. Column (1) of Table 2 shows the number of OHS specialists (from BLS) in each industry employed by establishments with 100 or more employees. Column (2) shows the corresponding percentage of the 29 in-scope industry total in each industry. Column (3) shows the percent of the establishments in the industry with at least one OHS specialist. The estimates in column (3) were obtained from the OES survey. Note that BLS could not provide us the data for the distribution of OHS specialists by establishment size classes due to confidentiality reasons. To obtain the estimates in column (1), we assumed that in a given industry, the proportion of the total OHS specialists employed in establishments with 100 or more employees is the same as the proportion of total employment in establishments with 100 or more employees. For example, we had an estimate that the employment in establishments with 100 or more employees makes up 72 percent of total employment in the coal mining industry (NAICS 2121). Then, we assumed that 72 percent of the OHS specialists in the coal mining industry work in establishments with 100 or more employees. We obtained a distribution of employment by establishment size classes for industries associated with the private sector from the BLS’s 2008 Quarterly Census of Employment and Wages and for the public sector from D&B.


The total sample size needed for each industry is derived to minimize the overall screener sample size while providing a total of 400 completed interviews. Thus, the size of screener sample needed in industry h,   , (column (4) of Table 2) is derived as:



where,

Yh is the number of OHS specialists employed in establishments with 100 or more employees in industry h;

θh is the proportion of establishments with one or more OHS specialist in industry h (column (3) divided by 100);

H is the number in-scope industries, that is, 29;

0.85 is the proportion of sampled establishments that are expected to complete the screener;

0.40 is the expected interview response rate for the establishments that are identified as having at least one OS&H professional.

The expected number of establishments completing the screener in industry h,   , is obtained, as:


The expected number of establishments identified in screener, as having one or more OS&H professionals in industry h,  , is obtained, as:



The expected number of completed interviews in industry h,  , is obtained, as:




Note that the estimate for the proportion of establishments in the industry with at least one OHS specialist, which was used in the screener sample size calculations obtained from the OES survey, includes establishments of all sizes. We expect that this proportion will be substantially higher for establishments with 100 or more employees. Thus, the required screener sample size estimates, as derived above, can be considered as an upper bound and we expect the actual screener sample size needed will be smaller. We will release the sample in at least two waves, using the first random wave to assess our assumptions. This will enable us to adjust the size of screener sample based on the results from the first wave.










Table 2. Sample sizes needed and the expected yields by 29 in-scope industries


















 

OHS specialist

 

Percent of

 

 

Expected

 


employment in

Percent of

establishments

Size of the

Expected

number of

Expected

Industry

establishments

total

reporting

screener

number of

eligible

number of

NAICS

with 100+

OHS specialist

at least one

sample

screener

screener

completed

Code

employees

employment

OHS specialist

needed

completes

completes

interviews

 

(1)

(2)

(3)

(4)

(5)

(6)

(7)









211100

271

0.99

2

91

77

2

1

212100

159

0.58

10

53

45

5

2

212200

144

0.53

14

49

41

6

2

213100

401

1.46

3

135

115

3

1

221100

621

2.27

4

209

178

7

3

311600

289

1.06

3

97

83

2

1

322100

142

0.52

12

48

41

5

2

324100

229

0.84

5

77

65

3

1

325100

342

1.25

7

115

98

7

3

325200

279

1.02

9

94

80

7

3

325400

321

1.17

6

108

92

6

2

331100

106

0.39

8

36

30

2

1

331300

113

0.41

9

38

32

3

1

331400

129

0.47

10

43

37

4

1

331500

130

0.48

4

44

37

1

1

336300

194

0.71

3

65

56

2

1

336400

610

2.23

5

205

175

9

3

482100

107

0.39

7

36

31

2

1

491100

202

0.74

2

68

58

1

0

492100

277

1.01

2

93

79

2

1

541600

972

3.55

1

327

278

3

1

541700

772

2.82

1

260

221

2

1

551100

1,006

3.67

2

338

288

6

2

611300

1,588

5.80

4

534

454

18

7

622100

3,007

10.98

18

1,012

860

155

62

622300

172

0.63

5

58

49

2

1

999100

4,817

17.60

17

1,621

1,378

234

94

999200

5,177

18.91

32

1,742

1,481

474

190

999300

4,796

17.52

2

1,614

1,372

27

11









Total

27,372

100.00

 

9,211

7,829

1,000

400



1.b.3 Stratification and sample size allocation


The establishments in the sampling frame will be stratified within each industry by four establishment size classes based on the number of employees at the establishment. The four size classes will be: 100-249 employees; 250-499 employees; 500-999 employees; and 1000 or more employees.


The sample size allocated to each industry, as described in Section 1.2 above, will be allocated to four size strata by Neyman allocation method, which provides an optimum allocation by minimizing the variance of the estimate for a given total sample size. The sample allocation for size stratum k in industry h, nhk, will be obtained, as:


 


where,

  is the total sample size allocated to industry h (see column (4) of Table 2 in Section 1.2),

Nhk is the number of in-scope establishments (with 100 or more employees) in size class k in industry h,

Shk is the standard deviation of the number of OH&S professionals in size class k in industry h.


We assume that number of OS&H professionals in establishments follows a Poisson distribution with a mean   and standard deviation  , where Yhk refers to the number of OS&H professionals in size class k in industry h and Nhk is the number of establishments in size class k in industry h.


Table 3 shows the allocation of the screener sample to size strata in each of the 29 industries. Table 3 shows the number of establishments (Nhk in the sample size allocation formula) and average number of OS&H professionals per establishment (square of   in the sample size allocation formula) in each industry by size stratum. Table 3 also shows the resulting sample size in each industry by size stratum (nhk in the sample size allocation formula) after allocating the total screener sample size of each industry to size classes by the Neyman allocation formula.


This sample size allocation results in oversampling of large establishments. The establishments in larger size classes will be selected with higher probability. The establishments within each industry by size stratum will be selected with equal probability.

Table 3. Allocation of the screener sample size to the establishment size strata





















 

 

 

 

 

 

 

 

 

 

 

 

 

 

 





Average number of





 

Industry

Number of establishments

OS&H professionals per establishment

 

Screener sample size

 

NAICS

Size of establishment

Size of establishment

 

 

Size of establishment

 

code

100-249

250-499

500-999

1000+

100-249

250-499

500-999

1000+

All

100-249

250-499

500-999

1000+

 





 



 


 

 

 

 

211100

152

63

20

16

0.467

1.054

2.214

5.504

91

40

25

12

15

212100

109

66

16

4

0.441

0.996

1.869

3.722

53

23

21

7

2

212200

31

17

22

6

0.678

1.402

2.583

6.998

49

13

10

17

8

213100

444

132

47

17

0.355

0.799

1.665

3.513

135

75

34

17

9

221100

565

150

95

33

0.364

0.850

1.625

4.021

209

107

43

38

21

311600

273

175

170

137

0.100

0.223

0.446

1.073

97

20

19

26

33

322100

133

81

59

17

0.200

0.446

0.871

1.620

48

15

14

14

5

324100

126

58

31

15

0.424

0.996

1.869

3.942

77

30

21

15

11

325100

223

79

30

12

0.527

1.160

2.260

5.165

115

58

31

16

10

325200

155

55

25

7

0.553

1.244

2.395

9.298

94

46

24

15

8

325400

243

131

74

44

0.198

0.435

0.840

3.501

108

34

27

21

26

331100

51

59

23

21

0.187

0.423

0.843

2.430

36

7

12

7

10

331300

114

42

20

6

0.318

0.686

1.501

2.965

38

18

10

7

3

331400

123

44

16

3

0.436

0.979

1.962

0.000

43

24

13

7

0

331500

254

100

37

8

0.180

0.410

0.804

1.729

44

22

13

7

2

336300

758

392

176

63

0.066

0.139

0.275

0.657

65

26

20

12

7

336400

312

131

87

77

0.205

0.462

0.900

5.307

205

59

37

35

74

482100

163

47

12

6

0.278

0.600

1.198

3.225

36

21

9

3

3

491100

811

130

69

43

0.097

0.238

0.493

1.365

68

41

10

8

8

492100

730

173

91

93

0.103

0.235

0.485

1.268

93

45

16

12

20

541600

872

207

68

21

0.490

1.140

2.145

7.555

327

202

73

33

19

541700

610

211

103

88

0.267

0.619

1.247

3.978

260

106

56

39

59

551100

2,295

843

431

204

0.118

0.264

0.527

1.399

338

150

83

60

46






Table 3 (continued). Allocation of the screener sample size to the establishment size strata





















 

 

 

 

 

 

 

 

 

 

 

 

 

 

 





Average number of





 

Industry

Number of establishments

OS&H professionals per establishment

 

Screener sample size

 

NAICS

Size of establishment

Size of establishment

 

 

Size of establishment

 

code

100-249

250-499

500-999

1000+

100-249

250-499

500-999

1000+

All

100-249

250-499

500-999

1000+

 





 



 


 

 

 

 

611300

429

413

307

212

0.244

0.526

0.996

4.532

534

89

126

129

190

622100

881

755

855

1,366

0.117

0.256

0.508

1.666

1,012

100

126

202

584

622300

200

98

38

23

0.163

0.355

0.738

3.264

58

22

16

9

11

999100

1,978

761

369

224

0.526

1.199

2.314

8.988

1,621

665

386

260

311

999200

2,071

797

386

234

0.540

1.230

2.375

9.224

1,742

714

415

279

334

999300

4,917

1,893

916

556

0.211

0.480

0.927

3.599

1,614

662

384

259

309

 





 



 


 

 

 

 

Total

20,025

8,107

4,595

3,557

 

 

 

 

9,211

3,433

2,074

1,565

2,138


1.b.4 Expected precision of the estimates

The most important population parameters of interest for the survey are the total number of OS&H professionals currently employed in the nation and the total number expected to meet future needs. This survey is expected to provide an estimate of the total number of OS&H professionals with a coefficient of variation (CV) of 5.1 percent.


The population subgroups of interest are OS&H professionals by specialty, including industrial hygiene, health physics, safety, ergonomics, occupational health nursing and occupational medicine. The precision of the estimates for these subgroups is expected to be lower.


In addition to the six OS&H specialties mentioned above, the survey will collect data on OS&H professionals in occupational health psychology, occupational injury prevention, and occupational epidemiology. However, because these three specialties are rare compared to the total population of OS&H professionals, we may not be able to provide stable estimates individually for each of them.


Below we describe the calculation of the expected precision of the total number of OS&H professionals stated above. Table 4 shows the expected number of completed interviews by industry and establishment size strata based on the screener sample size allocation presented in Table 3. First, variance of the population total estimate,  , was calculated, as:



where,

nhk is the expected number of completed interviews size class k in industry h ;

Nhk is the number of in-scope establishments (with 100 or more employees) in size class k in industry h (shown in Table 3);

  is the population variance of number of OH&S professionals in size class k in industry h (average number of OH&S professionals per establishment by size classes, shown in Table 3);

H and K are the numbers of industries and size classes, respectively.


Then, standard error of the estimate   was obtained as square root of  . CV of   was obtained as:   , where,   is the total number of OS&H specialists, 27,372, shown in the total row of column (1) of Table 2.


Table 4. Expected number of completed interviews by industry and establishment size

classes












 

 

 

 

 

 

 





 

 

Expected number of completed interviews

 

Industry

Industry

Size of establishment

 

NAICS code

total

100-249

250-499

500-999

1000+

 


 

 

 

 

211100

4

2

1

1

1

212100

2

1

1

0

0

212200

2

1

0

1

0

213100

6

3

1

1

0

221100

9

5

2

2

1

311600

4

1

1

1

1

322100

2

1

1

1

0

324100

3

1

1

1

0

325100

5

3

1

1

0

325200

4

2

1

1

0

325400

5

1

1

1

1

331100

2

0

1

0

0

331300

2

1

0

0

0

331400

2

1

1

0

0

331500

2

1

1

0

0

336300

3

1

1

1

0

336400

9

3

2

2

3

482100

2

1

0

0

0

491100

3

2

0

0

0

492100

4

2

1

1

1

541600

14

9

3

1

1

541700

11

5

2

2

3

551100

15

7

4

3

2

611300

23

4

5

6

8

622100

44

4

5

9

25

622300

3

1

1

0

0

999100

70

29

17

11

13

999200

76

31

18

12

14

999300

70

29

17

11

13

 


 

 

 

 

Total

400

149

90

68

93



2.0 Procedures for Collection of Information

Information will be collected from both groups (educational providers and employers) using similar strategies. This strategy includes the following steps:


  • Telephone screening of employer establishments to determine eligibility and to obtain contact information for the most appropriate respondent. We will contact sampled establishments by phone and attempt to speak with someone who can tell us whether the establishment employs any OS&H professionals – it is expected that this person will often be a Human Resources person. If the establishment does employ OS&H professionals, we will ask for the name and contact information for the person most knowledgeable about these professionals and/or who oversees OS&H activity for the establishment. This person will be the target respondent for the establishment. For a small number of establishments, we may be directed to more than one person. In such instances we will obtain contact information for other such persons.

  • Invitation Letter mail-out to all eligible establishments and educational providers inviting them to participate and directing them to the website where the questionnaire is located.

  • Data collection primarily by web questionnaire.

  • Follow-up with non-respondents once by mail two weeks after initial mailing. This will be followed by up to 7 attempted telephone contacts (with an offer to conduct the questionnaire by telephone at that point).


3.0 Methods to Maximize Response Rates and Deal with Non-response

3.a Methods to Maximize Response Rates

We will make every effort to maximize our response rates through efforts before questionnaire administration and after the initial administration. Our efforts include the following:


  • Correcting or collecting contact information for the appropriate respondent at the screening phase;

  • Offering 2 options for completing the questionnaire— web or telephone;

  • Conducting a quick mail follow-up for non-respondents; and

  • Repeated telephone follow-up for non-respondents with the offer of a telephone interview at that time.


3.b Methods to Deal with Non-Response

Although significant efforts will be made to obtain the highest possible response rates, as described above, some nonresponse is inevitable. We expect to have to address both unit and item nonresponse. In the former situation, a sampled unit, establishment or educational institution, does not participate in the survey while in the later, a responding unit provides incomplete data. We first discuss how we will deal with these two types of nonresponse and then we describe what we will do to assess the possibility of nonresponse bias.


Analyzing and Correcting for Nonresponse

To deal with unit nonresponse standard practice is to inflate survey weights to reflect this loss in participation. In addition, where possible, we benchmark the adjusted weights to known population totals, either by post-stratifying, raking or calibrating. This second step is contingent on having information, control counts or universe totals, available for the entire universe.


The first step in this process is to analyze the response pattern and determine the nature of adjustments that may help reduce potential biases. We will analyze the survey response rates by important characteristics of the sampled units. For establishments, we will tabulate response rates by NAICS codes, by size class and by other variables that may be important. Similar choices will be made for the provider survey. Once the response pattern is understood, a plan for weight adjustment can be finalized.


Survey weights of responding units are adjusted up to sample frame totals, within cells of similar units. Bias occurs when there is both a difference in propensity to respond as well as in the response. As a result, it is desirable to identify these adjustment cells by dividing the respondents into groups within which both the propensity to respond and the responses are similar. It is relatively easy to separate responding units into cells containing units with like propensity. We will use standard procedures such as CHAID or logistic regression models, to identify characteristics of the responding units that define these cells. We put into these models all the variables known about the responding units and assess their predictive power to model response propensity. Size of an establishment or educational facility, for example would be included in these models. NAICS categories would be included in the establishment models and ownership in the higher educational facility models.


Imputing for Item Nonresponse

Imputation methods are used to complete items that are not reported by respondents. At a minimum, we will perform imputation on any variable required by our weighting procedures. We will use a form of Hot Deck imputation, in which the items provided by a responding unit is copied into the missing item. Hot Deck is done carefully, matching a non-responding unit with one that is very similar on a defined set of characteristics. This ‘donation’ of information is monitored by our software to ensure that one donor’s response are not used unduly, and therefore does not over contribute to survey estimates.


Nonresponse Bias Assessment

We will take the following steps to assess the potential for bias caused by unit nonresponse. We will compare summed weights using base weights, using weights adjusted for nonresponse and finally using weights that have been benchmarked to universe totals. Any important differences that emerge from these comparisons can help to identify potential biases, as well as, assess the effectiveness in the weighting steps in reducing that potential.



4.0 Tests of Procedures

We pre-tested the survey instruments with fewer than 10 employers of OS&H professionals and representatives of OS&H educational programs to establish burden and to identify any sources of confusion or lack of clarity in the wording of the question. Respondents were emailed a draft version of the instrument, asked to fill it out, and discuss it with us in a brief teleconference call a few days later. In response to these pretests we improved the wording of several questions and clarified the definitions of key concepts that will be provided to survey respondents.


Once OMB approval is received, we will begin data collection following the steps outlined above in Section 2.0. After we have completed the steps for about 875 cases (expected to yield 100 completed surveys) we will review the procedures and data obtained to assess whether any adjustments in our methodology may be necessary. We will examine indicators such as: (a) the establishment eligibility rate (i.e., percentage of sampled establishments that employ at least one OS&H professional), (b) the response rate among eligible establishments (including the extent of break-offs occurring within the web survey), (c) numbers of professionals being reported across the key OS&H fields of interest to NIOSH, and (d) item nonresponse within the web survey. We do not anticipate that any substantial changes to the study methodology will result from this review. However, if modifications are necessary we will communicate with OMB before making the changes and proceeding with the remaining data collection.





5.0 Individuals Consulted on Statistical Aspects and Individuals Collecting or Analyzing the Data

Mr. David Morganstein

Vice President and Director of Statistical Staff

Westat


Mr. Huseyin Avni Goksel

Senior Statistician

Westat


Dr. James T. Wassell

Associate Director for Biostatical Science

DHHS/CDC/NIOSH/DSR/AFEB

Data Collection Designers and Supervisors:


Mr. Tim McAdams

Associate Director

Westat


Dr. Jeffrey Kerwin

Senior Study Director

Westat


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