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An Investigation of Holland Types and the Sixteen Personality Factor Questionnaire--Fifth Edition.

The authors investigated the stability of the published Sixteen Personality Factor Questionnaire--Fifth Edition (16PF; S. Conn & M. Rieke, 1994) predictors in predicting Holland types as measured by the Self-Directed self-di·rect·ed
Directed or guided by oneself, especially as an independent agent: the self-directed study of a language.

 Search (SDS 1. (company) SDS - Scientific Data Systems.
2. (tool) SDS - Schema Definition Set.
; J. Holland, B. Fritzsche, & A. Powell Powell See Osceola. , 1994). Because the majority of the published regression equations Regression equation

An equation that describes the average relationship between a dependent variable and a set of explanatory variables.
 contained unstable unstable,
adj 1. not firm or fixed in one place; likely to move.
2. capable of undergoing spontaneous change. A nuclide in an unstable state is called
radioactive. An atom in an unstable state is called
 predictors, the authors developed modified multiple regression Multiple regression

The estimated relationship between a dependent variable and more than one explanatory variable.
 equations using the more stable predictors. However, these equations, although statistically significant, shared less than 50% of the variance The discrepancy between what a party to a lawsuit alleges will be proved in pleadings and what the party actually proves at trial.

In Zoning law, an official permit to use property in a manner that departs from the way in which other property in the same locality
 with the criterion variable, suggesting limited practical utility or support for the domain overlap o·ver·lap
1. A part or portion of a structure that extends or projects over another.

2. The suturing of one layer of tissue above or under another layer to provide additional strength, often used in dental surgery.

 of the 16PF and the SDS. The authors recommend that the SDS be used when a measure of SDS types is needed.

The Sixteen Personality Factor Questionnaire--Fifth Edition (16PF; Conn & Rieke, 1994) is consistently rated as one of the most used and researched personality tests (Cattell Noun 1. Cattell - American psychologist (born in England) who developed a broad theory of human behavior based on multivariate research (1905-1998)
R. B. Cattell, Ray Cattell, Raymond B. Cattell, Raymond Bernard Cattell

, Eber EBER Electron Beam Electro-Reflectance , &Tatsuoka, 1970; Walsh Walsh has several meanings: Mathematics
  • Walsh matrix, an orthogonal matrix with several useful properties
  • Walsh transform, a linear transform based on the Walsh matrix
  • Walsh, Colorado
  • Walsh County, North Dakota
 & Betz Betz may refer to:
  • GE Betz, a water treatment company
People with the surname Betz:
  • Albert Betz, a physicist
  • Carl Betz, an actor
  • Pauline Betz, a tennis player
  • Peter Betz, a businessman
  • Vladimir Alekseyevich Betz, Russian scientist
, 1995). It contains 16 bipolar (1) See bipolar transmission.

(2) One of two major categories of transistor; the other is "field effect transistor" (FET). Although the first transistors and first silicon chips were bipolar, most chips today are field effect transistors wired as CMOS logic, which
 scales (called "primary factors") and several validity scales, with 15 of the factors measuring personality traits and 1 factor measuring cognitive ability or reasoning ability (Conn & Rieke, 1994). One reason the 16PF has been such a popular measure is that validated val·i·date  
tr.v. val·i·dat·ed, val·i·dat·ing, val·i·dates
1. To declare or make legally valid.

2. To mark with an indication of official sanction.

 special scores greatly expand the utility of the 16PF for the counselor. These scores allow the instrument to assess the role of personality structure in leadership, creativity, and specific occupations. Thus, the instrument not only allows the client's interests and abilities to be examined but also allows his or her personality to be taken into consideration during occupational decision making. For example, a client may have interests that are similar to those of a surgeon but may have a score on the 16PF that indicates a great degree of impulsivity and impatience. Of course, this characteristic would need to be addressed during the career decision-making decision-making,
n the process of coming to a conclusion or making a judgment.

decision-making, evidence-based,
n a type of informal decision-making that combines clinical expertise, patient concerns, and evidence gathered from
 process with this client. Although certainly not all clients would benefit from such a discussion, many occupations (e.g., police officer, clergy, or airline pilot) do require that the personality of the applicant be taken into consideration.

One set of special scores obtained from the 16PF, available by computer scoring, is the prediction of Holland's occupational types. The intent of these special scores is to allow the career counselor to explore the client's interests and personality structure in the career counseling Noun 1. career counseling - counseling on career opportunities
counseling, counselling, guidance, counsel, direction - something that provides direction or advice as to a decision or course of action
 process (Conn & Rieke, 1994). Using the 16PF and the Self-Directed Search (SDS; Holland, Fritzsche, & Powell, 1994) in career counseling requires understanding the overlap of personality and interests, in general, and the ability of the 16PF to predict the SDS codes, in particular.

The field of career counseling continues to examine the relationship between personality and interests and to debate whether there is an overlap of personality and interests or whether these constructs are largely separate domains (Holland, Fritzsche, et al., 1994; Janda The village of Jadna(Gilan,Gelan) is the district center of the Gelan District,Ghazni Province,Afghanistan.It is situated in the central part of the district on  at 1983 m altitude.The houses are made of mud bricks and the streets are unpaved. , 1998; Oliver Ol·i·ver   , Joseph Known as "King Oliver." 1885?-1938.

American jazz musician and composer who had a great influence on the style of Louis Armstrong. His Creole Jazz Band was the first Black group to make jazz recordings.
, Lent Lent [Old Eng. lencten,=spring], Latin Quadragesima (meaning 40; thus the 40 days of Lent). In Christianity, Lent is a time of penance, prayer, preparation for or recollection of baptism, and preparation for the celebration of Easter. , & Zack, 1998; Young & Chen, 1999; Zunker, 1994). Because the 16PF is one of the most commonly used personality measures that has application to career counseling, the overlap of the 16PF and interests may be of particular importance to career counselors (Oliver et al., 1998; Young & Chen, 1999; Zunker, 1994). The proposed overlap of interests may be important for several reasons, but arguably ar·gu·a·ble  
1. Open to argument: an arguable question, still unresolved.

2. That can be argued plausibly; defensible in argument: three arguable points of law.
 one of the more important reasons for the career counselor may be the utility of making assumptions about the personality of the client from interest inventory results or of making assumptions about interests given a client's personality structure. If empirical support for the overlap of the personality and interest domains can be de monstrated, then the career counselor may be able to discuss the client's personality characteristics that may be important for a specific career, given the results of an interest inventory. Without the establishment of empirical support for the overlap of these domains, making any assumptions about personality from interests, or interests from personality, is risky, at best.

An additional possible benefit of empirical support for the overlap of interests and personality domains, especially in today's HMO-styled market where assessment time is often limited, is a reduction in testing time in situations when information about personality and interests is beneficial. It can certainly be argued that not all career decisions would benefit from data on personality and interests; however, for situations in which it would be beneficial, a substantial reduction in resources may be possible. The Holland types were likely choices to examine the overlap of more general personality and occupational types because Holland conceptualized these occupational types as "personality types" (Holland, Fritzsche, et al., 1994, p. 1). He contended that there are six occupational personality types, found in both people and the environment, that can be described using a hexagonal hex·ag·o·nal  
1. Having six sides.

2. Containing a hexagon or shaped like one.

3. Mineralogy
 model (Holland, Fritzsche, et al., 1994). Holland further contended that the better the match between a person's personality typ e and his or her work environment, the more likely the individual is to find the occupation satisfying. Because Holland conceived of his model as a personality model, we believed that it seemed logical to examine the overlap of interests and personality traits.

The authors of the 16PF have attempted to examine the possible overlap of the personality domain with interests (Conn & Rieke, 1994). In doing so, they used 16PF scores to predict Holland types that would be obtained from the SDS (Karol Karol is a Polish and Slovak version of the name Charles or Carl. People with the given first name Karol
  • Karol Adamiecki, Polish economist, engineer and management researcher
  • Karol Beck, a Slovak tennis player
  • Karol J.
, 1994). In the development of regression equations, one of the most critical aspects is the cross-validation Cross-validation, sometimes called rotation estimation[1] [2] [3], is the statistical practice of partitioning a sample of data into subsets such that the analysis is initially performed on a single subset, while the other subset(s) are  process. Cross-validation demonstrates that the predictor variables Noun 1. predictor variable - a variable that can be used to predict the value of another variable (as in statistical regression)
variable quantity, variable - a quantity that can assume any of a set of values
 are stable across various samples from the target population. The stability of the predictors is vital to any use of the derived scores, because the applicability of the equations beyond the sample used to develop them is not known without cross-validation research (Hair, Anderson Anderson, river, Canada
Anderson, river, c.465 mi (750 km) long, rising in several lakes in N central Northwest Territories, Canada. It meanders north and west before receiving the Carnwath River and flowing north to Liverpool Bay, an arm of the Arctic
, Tatham Tatham may mean: Places
  • Tatham, Lancashire, a civil parish in Lancashire, England.
  • Tatham, New South Wales, a locality in Richmond Valley.
  • Tatham School, an elementary school in West Springfield, Massachusetts.
  • William M.
, & Black, 1998; Nunnally & Bernstein Bern·stein   , Leonard 1918-1990.

American conductor and composer who wrote numerous choral and symphonic works, including Kaddish (1963), and musicals, notably On the Town (1944) and West Side Story (1957).
, 1994). Despite the recommendation for continued cross-validation of regression equations, to date, limited data on the cross-validation of these equations are available (Gonn & Rieke, 1994; Karol, 1994). Therefore, additional cross-validation research regarding these special scores is needed.

The primary purpose of this study was to investigate the stability of the published 16PF predictor variables used in the regression equations to estimate SDS Holland types when a different sample of adults was surveyed. A secondary purpose of this study was to examine the domain overlap of the 16PF and SDS.



The sample used in this study consisted of the responses from 234 volunteers. Of these volunteers, 109 (47%) were from southern Indiana Southern Indiana, in the United States, is notable because it is culturally distinct from the rest of the state. The area's geography has led to a blend of Northern and Southern culture that is not found in the rest of Indiana. , southern Illinois Illinois, river, United States
Illinois, river, 273 mi (439 km) long, formed by the confluence of the Des Plaines and Kankakee rivers, NE Ill., and flowing SW to the Mississippi at Grafton, Ill. It is an important commercial and recreational waterway.
, or northern Kentucky Kentucky, state, United States
Kentucky (kəntŭk`ē, kĭn–), one of the so-called border states of the S central United States. It is bordered by West Virginia and Virginia (E); Tennessee (S); the Mississippi R.
; 59 (25%) were from northeastern Ohio or northwestern Pennsylvania Pennsylvania (pĕnsəlvā`nyə), one of the Middle Atlantic states of the United States. It is bordered by New Jersey, across the Delaware River (E), Delaware (SE), Maryland (S), West Virginia (SW), Ohio (W), and Lake Erie and New York ; and 65 (28%) were from southern Florida Florida, state, United States
Florida (flôr`ĭdə, flŏr`–), state in the extreme SE United States. A long, low peninsula between the Atlantic Ocean (E) and the Gulf of Mexico (W), Florida is bordered by Georgia and
. Participants ranged in age from 18 to 69 years old. One person was not clear regarding location. The mean age was 27.9 years (SD = 10).

Of the participants, 29% (n = 67) were men and 71% (n = 167) were women. To obtain as representative a sample as possible, minority community and university organizations in several locations were contacted and their members were invited to participate. The reported racial heritages of the participants were 83% Whites (n = 194), 9% Blacks (n = 20), 6% Hispanics (n = 14), 2% Asians (n = 5), and 0.4% Native American American, river, 30 mi (48 km) long, rising in N central Calif. in the Sierra Nevada and flowing SW into the Sacramento River at Sacramento. The discovery of gold at Sutter's Mill (see Sutter, John Augustus) along the river in 1848 led to the California gold rush of  (n = 1). The participants' mean educational level was 14.9 years (2 years of college; SD = 2.5). One participant did not report his or her educational level.

There were 58% (n = 135) undergraduate and graduate students and 42% (n = 98) community members (persons not enrolled in classes) in the sample. One participant's group membership was not indicated. To expand the diversity of interests in the sample, university participants were solicited from programs in art, music, accounting, business management, counseling, elementary education elementary education
 or primary education

Traditionally, the first stage of formal education, beginning at age 5–7 and ending at age 11–13.
, secondary education, and special education.


The 16PF. The 16PF is designed to measure normal personality traits (Gattell et al., 1970; Conn & Rieke, 1994). It has been revised several times over the years, primarily to update norms, but more recently to update language and to improve the psychometric psy·cho·met·rics  
n. (used with a sing. verb)
The branch of psychology that deals with the design, administration, and interpretation of quantitative tests for the measurement of psychological variables such as intelligence, aptitude, and
 qualities of the tool. The 16PF contains 16 bipolar scales (called "primary factors"), 5 global factor scales, and several validity scales. Fifteen of the primary factors and the 5 global factors measure personality traits; 1 factor measures cognitive ability. The stability coefficients for the personality factors and validity scales range from r = .69 to r .91 for 2 weeks, with the range of r = .56 to r = .82 for 2 months. The internal consistency In statistics and research, internal consistency is a measure based on the correlations between different items on the same test (or the same subscale on a larger test). It measures whether several items that propose to measure the same general construct produce similar scores.  of the primary factors and validity scales ranged from [alpha] = .66 to [alpha] = .87 (Conn & Rieke, 1994).

There are extensive supportive validity data reported in the technical manual for the 16PF. Data on the factor structure, item analysis, and relationships of the 16PF to other measures are also included in the manual (Conn & Rieke, 1994. Using data from a sample of 194 individuals, Karol (1994) developed equations, using a multiple regression procedure, for predicting SDS Holland codes from 16PF data.

The SDS. The SDS is a widely used interest inventory, developed by Holland, that was designed to aid in the career decision-making process (Holland, Fritzsche, et al., 1994; Holland, Powell, & Fritzsche, 1994; Walsh & Betz, 1995). The SDS has six scales that are based on Holland's theory of career decision making. Holland described the six scales using a hexagonal model that symbolizes the relationship between the personality types (Holland, Fritzsche, et al., 1994; Holland, Powell, et al., 1994).

The stability of the six SDS scales ranged from r = .76 to r= .89 over 4 to 12 weeks. Considerable validity data are reported in the manuals, including examinations of the content, relationship to other interest measures, relationship to personality measures, and prediction of occupational satisfactions and fit (Holland, Fritzsche, et al., 1994; Holland, Powell, et al., 1994).


Data for this study were collected as part of a group of studies on the 16PF being conducted by the first author. Sample size was preestablished, using procedures recommended by experts in the application of this methodology (Hair et al., 1998; Nunnally & Bernstein, 1994).

The administration packets included the 16PF, SDS, demographics The attributes of people in a particular geographic area. Used for marketing purposes, population, ethnic origins, religion, spoken language, income and age range are examples of demographic data.  sheet, and other instruments, which were placed in an envelope in counterbalanced coun·ter·bal·ance  
1. A force or influence equally counteracting another.

2. A weight that acts to balance another; a counterpoise or counterweight.

 order. A description of the study was either handed to or read to participants before they opened the envelope. Approximately 60% of the participants completed the inventory in a group setting, and the other 40% took the packet home to complete it. Two hundred and sixty packets of materials were distributed; 234 were returned with completed 16PFs and SDSs, yielding a return rate of 90%.

Data Analysis

Data analysis was performed using SYSTAT SYSTAT is a statistics and statistical graphics software package, developed by Leland Wilkinson in the late 1970's, who was at the time an assistant professor of psychology at the University of Illinois at Chicago. Systat was incorporated in 1983 and grew to over 50 employees.  9.0 for Windows (SPSS A statistical package from SPSS, Inc., Chicago ( that runs on PCs, most mainframes and minis and is used extensively in marketing research. It provides over 50 statistical processes, including regression analysis, correlation and analysis of variance. , 1999). The 16PF raw scale scores were converted to sten scores A sten score is a standard score often used in the interpretation of psychological tests. It has a mean of 5.5 and a standard deviation of 2. Thus, approximately 95% of respondents would typically fall between two standard deviations of the mean (i.e., 1.5 and 9.5). , using the combined population norms provided by the publisher (Conn & Rieke, 1994).

Because this study was designed to examine the effect of sampling error (or bias) on the stability of predictors in multiple regression equations, an established procedure to detect error in regression regression, in psychology: see defense mechanism.

In statistics, a process for determining a line or curve that best represents the general trend of a data set.
 formulas was applied; the procedure was first developed by Cleary Clea·ry   , Beverly Born 1916.

American author of children's books. Her works include a series of humorous novels featuring Henry Huggins.
 (1968) and further refined by others (Hair et al., 1998; Nunnally & Bernstein, 1994). Sampling bias (error) is suggested if the predictors proposed to make up the regression equation do not meet two criteria in the cross-validation sample. The first criterion is that the predictor variable must significantly enter into the regression equation when using the cross-validation sample. Second, the predictor variable must enter into the regression equation from the cross-validation sample in the same direction (positive or negative) as in the developmental sample (Hair et al., 1998; Nunnally & Bernstein, 1994).

Two regression procedures (models) were calculated to evaluate whether the predictor variables that were reported by Karol (1994) met the two cross-validation criteria. The first regression model (free model) was calculated using a forward stepwise stepwise

incremental; additional information is added at each step.

stepwise multiple regression
used when a large number of possible explanatory variables are available and there is difficulty interpreting the partial regression
 procedure with the entry and removal criterion set to .10 as was done during development (Karol, 1994). Stability of the predictors was supported if the predictor entered into the free model as it had in Karol's study. The second regression model (forced model) was constructed by using the published predictors for each Holland type to calculate a multiple regression equation. This forced all the prior established predictors into a model to determine whether, if they had entered into the equation, they would have done so in the same direction, using data from the sample of individuals who participated in this study. Correct entry into the forced model provided less support for the stability of the predictors than did entry into the free model. Stability of the predi ctors was best supported if the predictor variables entered into the free model equation and did so in the same direction as found in Karol's study (Hair et al., 1998; Nunnally & Bernstein, 1994).

A cross-validated equation was calculated using predictors that were considered stable from Karol's (1994) study and the free model. These represent the cross-validated models (Cleary, 1968; Hair et al., 1998; Nunnally & Bernstein, 1994). The cross-validated model was considered statistically significant if it provided a prediction that was substantially greater than chance, as determined by the Fstatistic having a p < .05.

Domain overlap can be considered an issue of practical significance because two tools or procedures are attempting to measure a common construct or domain in regression models (Nunnally & Bernstein, 1994). The practical utility of two measures being considered interchangeable in·ter·change·a·ble  
That can be interchanged: interchangeable items of clothing; interchangeable automotive parts.

 has been examined using a number of methods, but most commonly by examining alternate form reliability (Cicchetti, 1994; Janda, 1998; Nunnally & Bernstein, 1994). Two tools or procedures are accepted as sharing adequate domain, or seen as alternate forms, if they have 50% or more shared variance. This provides initial evidence of domain overlap. The shared variance of regression models is best estimated by examining the adjusted [R.sup.2]. The cross-validated multiple regression equations were considered practically significant if they shared 50% or more variance (adjusted [R.sup.2] > .50) with the SDS scale they were predicating.


The means and standard deviations In statistics, the average amount a number varies from the average number in a series of numbers.

(statistics) standard deviation - (SD) A measure of the range of values in a set of numbers.
 for the 16PF and the SDS are provided in Table 1. The results of examining the stability of the predictors from the primary and global factor models are summarized in Table 2. These data supported the stability of the global factor predictors for the SDS Realistic, Artistic, and Conventional scales. These data supported the primary factor model for the SDS Enterprising en·ter·pris·ing  
Showing initiative and willingness to undertake new projects: The enterprising children opened a lemonade stand.
 scale as being composed of stable predictors.

Table 3 presents the adjusted [R.sup.2]s for both the 16PF global factor and 16PF primary factor cross-validated multiple regression equations. None of the multiple regression equations met the criteria for practical significance in predicting the SDS scales from 16PF factors of adjusted [R.sup.2] > .50.


The primary purpose of this study was to investigate, using a different sample of individuals than had been used in previous studies, the stability of the 16PF predictor variables in predicting Holland types, as measured by the SDS. If the stability of the predictor variable could not be demonstrated, the application of the equation in a real-life real-life  
Actually happening or having happened; not fictional: a documentary with footage of real-life police chases. 
 situation would not be supported. This would mean that any equation would be different for various groups of adults and that no consistent prediction of SDS types would be possible.

The results of this study indicate that the published global factor multiple regression equations for the Realistic, Artistic, and Conventional scales were constructed from stable predictor variables. Three of the published global factor multiple regression equations contained predictors that failed to be supported as stable in this study. Of the six published multiple regression equations using the l6PF primary factors to predict SDS scores, only the Enterprising equation was found to be constructed completely from stable predictors. These data indicate that if a prediction of SDS scale scores from the 16PF is needed, the cross-validated multiple regression equations reported in Table 3 contain predictors known to be more stable, and, as such, are preferable to Karol's (1994) equations. Because there were statistically significant regression equations that could be constructed from the 16PF, this provided some support for the potential of the 16PF to have utility in exploring SDS types. However, before such a potential can be considered meaningful and as having practical utility in career counseling, the establishment of alternate form reliability also needs to support such a procedure. Furthermore, these results suggest the need to continue to refine the regression models using other samples and further research into the relationship of the Holland types and the 16PF.

In order to examine the practical utility of the regression equations for the SDS that were constructed from the 16PF, one method is to examine adequate alternate form reliability. When the alternate form reliability of the two procedures was examined, no support was found for the interchangeability in·ter·change·a·ble  
That can be interchanged: interchangeable items of clothing; interchangeable automotive parts.

 of the two procedures. The results of this study suggest that statistically significant and stable regression models that predict SDS scale scores can be constructed from 16PF scores. This finding provides evidence that there is some shared domain between the SDS and the 16PF. However, neither Karol's (1994) results nor the results from this study provided support for the practical significance of any model. Thus, although there is likely some shared domain between the two measures, it is insufficient to equate e·quate  
v. e·quat·ed, e·quat·ing, e·quates
1. To make equal or equivalent.

2. To reduce to a standard or an average; equalize.

 them as alternate forms for one another. This suggests that although the overlap may be of interest to researchers, the application of these equations by the career counselor in a real-life setting was not supported by these data. Thus, when measures of interests and personality are important to the career decision-making process, both the 16PF and the SDS would need to be administered.

To ensure that the lack of utility of the 16PF in measuring SDS scores was not an artifact A distortion in an image or sound caused by a limitation or malfunction in the hardware or software. Artifacts may or may not be easily detectable. Under intense inspection, one might find artifacts all the time, but a few pixels out of balance or a few milliseconds of abnormal sound  of the statistical procedure of multiple regression, classical item analysis was used to examine these data. These results further supported the finding that although some degree of content overlap was present, it was insufficient to have practical utility (Nunnally & Bernstein, 1994). The lack of domain overlap was most evident in the prediction of the SDS Conventional scale score. There was less than 5% shared variance between the cross-validated multiple regression equations and the SDS Conventional scale score. The low predictive power The predictive power of a scientific theory refers to its ability to generate testable predictions. Theories with strong predictive power are highly valued, because the predictions can often encourage the falsification of the theory.  of the cross-validated multiple regression was consistent with the general lower predictive power of the SDS Conventional scale in this study and with the results reported by Karol (1994).

In summary, these results have implications for the practitioner and for future researchers. For the practitioner, these results suggest that although the 16PF may have some domain overlap with the SDS, the overlap is too small to be of utility in an applied setting.

Researchers may note, however, that cross-validated statistically significant regression equations could be constructed. This suggests that at least some of the domain of personality, as measured by the 16PF and the SDS, was present. These data were consistent with Karol's (1994) findings that the Realistic, Enterprising, Social, and Artistic types had the largest overlap with personality, whereas the Conventional type had the least overlap. This suggests that although some Holland types may have overlap with 16PF personality traits, others may have little overlap. Additional research should examine the possibility that, perhaps as we have defined personality and interests, the overlap is only in some areas.

This study was limited in several ways. Although this sample was more representative of the general population of the United States United States, officially United States of America, republic (2005 est. pop. 295,734,000), 3,539,227 sq mi (9,166,598 sq km), North America. The United States is the world's third largest country in population and the fourth largest country in area.  than the sample used in previous research, the study needs to be replicated using more representative samples. Furthermore, it is important to remember that as with any assessment tool, application and interpretation of the 16PF and SDS need to take place on the basis of sound clinical practice and an understanding of assessment.

Dale R. Pietrzak is an assistant professor in the Department of Counseling and Psychology in Education at the University of South Dakota Nomenclature
  • The abbreviation USD is the most widely used title of the school. (The University of San Diego also employs the same abbreviation.)
  • It is also often referred to as "the U" by locals.
  • "usd" is used only in Internet domain names.
, Vermillion. Betsy Betsy is an English name for females, used as a nickname for Elizabeth. It is also a surname. Famous uses or users of Betsy include:
  • Betsy McCaughey
  • Betsy Tacy
  • Betsy Boze
  • Betsy Clifford
  • Betsy McLaughlin
  • Betsy Joslyn
  • Betsy Holden
  • Hurricane Betsy
 J. Page is an assistant professor in the Department of Counseling and Human Development Services at Kent State University, Kent, Ohio Kent is a city in Portage County, Ohio, United States. The population was 27,906 at the 2000 census, making it the county's largest city. Kent is home to the main campus of Kent State University. Nearby metropolitan areas include Akron, Cleveland, Canton, and Youngstown-Warren. . Correspondence regarding this article should he sent to Dale R. Pietrzak, University of South Dakota, 414 East Clark Street, Vermillion, SD 57069 (e-mail: See .edu.

(networking) edu - ("education") The top-level domain for educational establishments in the USA (and some other countries). E.g. "". The UK equivalent is "".


Catrell, R., Eber, H., & Tatsuoka, M. (1970). Handbook
For the handbook about Wikipedia, see .

This article is about reference works. For the subnotebook computer, see .
"Pocket reference" redirects here.
 for the J6PF. Champaign Champaign (shămpān`), city (1990 pop. 63,502), Champaign co., E central Ill.; inc. 1860. It adjoins the city of Urbana and is a commercial and industrial center in a fertile farm area. The Univ. , IL: Institute for Personality and Ability Assessment.

Cicchetti, D. V. (1994). Guidelines guidelines, a set of standards, criteria, or specifications to be used or followed in the performance of certain tasks.
, criteria, and rules of thumb For evaluating normed and standardized standardized

pertaining to data that have been submitted to standardization procedures.

standardized morbidity rate
see morbidity rate.

standardized mortality rate
see mortality rate.
 assessment instruments in psychology. Psychological Assessment, 6, 284-290.

Cleary, A. (1968). Test bias: Prediction of grades of Negro Negro or Negroid: see race.  and White students in integrated colleges. Journal of Educational Measurement, 10, 43-56.

Conn, S., & Rieke, M. (Eds.). (1994). l6PFfifth edition: Technical manual. Champaign, IL: Institute for Personality and Ability Testing.

Hair, J., Anderson, R., Tatham, R., & Black, W. (1998). Multivariate The use of multiple variables in a forecasting model.  data analysis (5th ed.). Upper Saddle River Saddle River may refer to:
  • Saddle River, New Jersey, a borough in Bergen County, New Jersey
  • Saddle River (New Jersey), a tributary of the Passaic River in New Jersey
, NJ: Prentice Hall Prentice Hall is a leading educational publisher. It is an imprint of Pearson Education, Inc., based in Upper Saddle River, New Jersey, USA. Prentice Hall publishes print and digital content for the 6-12 and higher education market. History
In 1913, law professor Dr.

Holland, J., Fritzsche, B., & Powell, A. (1994). Self-Directed Search: Technical manual. Odessa, FL: Psychological Assessment Resources.

Holland, J., Powell, A, & Fritzsche, B. (1994). Self-Directed Search: Professional user's guide. Odessa, FL: Psychological Assessment Resources.

Janda, L. (1998). Psychological testing psychological testing

Use of tests to measure skill, knowledge, intelligence, capacities, or aptitudes and to make predictions about performance. Best known is the IQ test; other tests include achievement tests—designed to evaluate a student's grade or performance
: Theory and application. Boston: Allyn & Bacon.

Karol, D. (1994). Holland occupational typology typology /ty·pol·o·gy/ (ti-pol´ah-je) the study of types; the science of classifying, as bacteria according to type.


the study of types; the science of classifying, as bacteria according to type.
 and the 16PF. In S. Conn & M. Rieke (Eds.), l6PF fifth edition: Technical manual (pp. 2 13-235). Champaign, IL: Institute for Personality and Ability Testing.

Nunnally, J., & Bernstein, I. (1994). Psychometric theory (3rd ed.). New York New York, state, United States
New York, Middle Atlantic state of the United States. It is bordered by Vermont, Massachusetts, Connecticut, and the Atlantic Ocean (E), New Jersey and Pennsylvania (S), Lakes Erie and Ontario and the Canadian province of
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Means and Standard Deviations for 16PF-5th Edition and SDS

Scale/Factor              n    M     SD

16PF-5th Edition
  A Warmth               230   6.3   1.8
  B Reasoning            229   6.2   1.7
  C Emotional stability  230   5.6   1.8
  E Dominance            230   5.2   2.0
  F Liveliness           230   6.0   1.9
  G Rule-consciousness   229   5.4   1.9
  H Social boldness      230   5.7   2.0
  I Sensitivity          230   6.4   1.8
  L Vigilance            230   5.3   2.0
  M Abstractness         230   5.6   1.9
  N Privateness          230   5.0   2.1
  O Apprehension         230   5.8   1.8
 Q1 Open to change       230   5.7   2.2
 Q2 Self-Reliance        230   5.3   1.8
 Q3 Perfectionism        230   5.0   2.1
 Q4 Tension              230   5.5   1.8
 Extroversion            230   6.1   1.9
 Anxiety                 230   5.5   2.0
 Tough mindedness        230   4.8   2.0
 Independence            230   5.4   1.9
 Self-Control            229   5.1   1.8
Self-Directed Search
 Realistic               234  17.2  10.7
 Investigative           234  21.9  10.6
 Artistic                234  24.2  12.0
 Social                  234  36.3   8.9
 Enterprising            234  25.9   9.0
 Conventional            234  21.7  10.8

Note. 16PF-5th Edition = Sixteen Personality Factor Questionnaire-Fifth

SDS = Self-Directed Search.

For the standardization sample, M = 5.5 and SD = 2.0

Regression Results of 16PF-5th Edition for SDS

Holland Type (a)            F             R

Global Factors
 Realistic (n = 229)
  Predicted (c)            10.7 (**)  .43 - .47
  Free (d)                 12.9 (**)     .47
  Forced (e)               12.9 (**)     .47
 Investigative (n = 230)
  Predicted (c)             5.7 (**)  .30 - .36
  Free (d)                  7.2 (**)     .30
  Forced (e)                4.6 (**)     .31
 Artistic (n = 230)
  Predicted (c)            70.9 (**)  .51 - .52
  Free (d)                 38.9 (**)     .59
  Forced (e)              106.7 (**)     .57
 Social (n = 229)
  Predicted (c)            27.2 (**)  .53 - .55
  Free (d)                 23.6 (**)     .54
  Forced (e)               28.9 (**)     .53
 Enterprising (n = 230)
  Predicted (c)            27.0 (**)  .52 - .55
  Free (d)                 24.7 (**)     .42
  Forced (e)               16.6 (**)     .43
 Conventional (n = 229)
  Predicted (c)            19.7 (**)  .39 - .41
  Free (d)                  6.9 (**)     .24
  Forced (e)                6.9 (**)     .24
Primary Factors
 Realistic (n = 229)
  Predicted (c)            18.2 (**)  .57 - .54
  Free (d)                 26.8 (**)     .61
  Forced (e)               25.4 (**)     .60
 Investigative (n = 229)
  Predicted (c)            12.8 (**)  .57 - .52
  Free (d)                 11.3 (**)     .48
  Forced (e)                8.4 (**)     .46
 Artistic (n = 230)
  Predicted (c)            21.4 (**)  .56 - .53
  Free (d)                 24.1 (**)     .59
  Forced (e)               27.7 (**)     .57
 Social (n = 229)
  Predicted (c)            21.5 (**)  .60 - .57
  Free (d)                 21.2 (**)     .60
  Forced (e)               22.7 (**)     .58
 Enterprising (n = 230)
  Predicted (c)            20.7 (**)  .60 - .57
  Free (d)                  9.4 (**)     .51
  Forced (e)               12.1 (**)     .46
 Conventional (n = 222)
  Predicted (c)            16.6 (**)  .46 - .43
  Free (d)                  6.9 (**)     .29
  Forced (e)                5.4 (**)     .26

Holland Type (a)                   16PF Factors (b)

Global Factors
 Realistic (n = 229)
  Predicted (c)                 TM+, IN+, AX-, EX-, SC-
  Free (d)                      IN+, TM+, EX-, AX-, SC-
  Forced (e)                    IN+, TM+, EX-, AX-, SC-
 Investigative (n = 230)
  Predicted (c)             EX-, SC-, IN+ (f), TM+, AX- (f)
  Free (d)                           EX-, IN+, AX-
  Forced (e)                EX-, IN+, AX-, TM- (g), SC+ (g)
 Artistic (n = 230)
  Predicted (c)                           TM-
  Free (d)                           TM-, EX-, IN+
  Forced (e)                              TM-
 Social (n = 229)
  Predicted (c)                    EX+, TM-, SC+ (f)
  Free (d)                        TM-, EX+, IN+, SC+
  Forced (e)                         TM-, EX+, SC+
 Enterprising (n = 230)
  Predicted (c)                    IN+, TM+(f), EX+
  Free (d)                             IN+, TM+
  Forced (e)                       IN+, TM+, EX+ (g)
 Conventional (n = 229)
  Predicted (c)                        SC+, TM+
  Free (d)                             SC+, TM+
  Forced (e)                           SC+, TM+
Primary Factors
 Realistic (n = 229)
  Predicted (c)                  I-, A-, O-, Q1+, Q4-
  Free (d)                        I-, Q1+, A-, G+, H+
  Forced (e)                 I-, Q1+, A-, Q4- (g), O- (g)
 Investigative (n = 229)
  Predicted (c)            A-, I-, B+, Q4-, M+, N- (f), Q1+
  Free (d)                     A-, Q1+, B+, O+, Q4-, I-
  Forced (e)              A-, B+, Q1+, Q4-, I-, N+ (g), M+(g)
 Artistic (n = 230)
  Predicted (c)                     I+, M+, H+, Q1+
  Free (d)                       I+, Q1+, M+, Q2+, E+
  Forced (e)                      I+, Q1+, M+, H+ (g)
 Social (n = 229)
  Predicted (c)               A+, H+, G+ (f), C- (f), Q1+
  Free (d)                      A+, Q1+, H+, E+, N+, I+
  Forced (e)                  A+, Q1+, H+, C- (g) G+ (g)
 Enterprising (n = 230)
  Predicted (c)                  A+, E+ H+, I-, N+ (f)
  Free (d)                 E+, A+, I-, H+, C-, N+, Q3+, Q1+
  Forced (e)                      E+, A+, I-, N+, H+
 Conventional (n = 222)
  Predicted (c)                       M-, Q3+, I-
  Free (d)                            M-, L+, H-
  Forced (e)                        Q3+, I-, M- (g)

Note. See Table 1 Note.

(a)Scales in order of magnitude of Standardized beta weights; + or - =
direction scale entered equation.

(b)Letters = scale names (Conn & Rieke, 1994).

(c)Conn & Rieke (1994).

(d)Model developed from sample when forward stepwise procedure and .10
entry/removal criteria used.

(e)When predicted scales placed into model and regression equation

(f)Indicates prediction that scale acts as suppressor variable (Karol,

(g)ns, p > 10.

(*)p < .05.

(**)p < .01.

Cross-Validated Regression of SDS From 16PF-5th Edition

SDS Scale                            A-[R.sup.2] (R) (a)   M    SD

Global factor score equations (**)
   Realistic (n = 229)                  .21 (.47)         17.6  5.1

   Investigative (n = 230)              .08 (.30)         21.7  3.1

   Artistic (n = 230)                   .32 (.57)         24.5  6.7
   Social (n = 229)                     .27 (.53)         36.2  4.6

   Enterprising (n = 230)               .17 (.42)         25.9  9.0

   Conventional (n = 229)               .05 (.24)         21.7  2.6

Primary factor score equations (**)
   Realistic (n = 230)                  .35 (.60)         17.1  6.5

   Investigative (n = 229)              .19 (.46)         21.4  4.9

   Artistic (n = 230)                   .32 (.57)         24.3  6.8

   Social (n = 230)                     .32 (.58)         36.7  9.0

   Enterprising (n = 230)               .20 (.46)         26.0  4.2

   Conventional (n = 222)               .03 (.19)         22.0  1.9

SDS Scale                              SEE  16PF Equation (b)

Global factor score equations (**)
   Realistic (n = 229)                9.53  (-1.9*EX) + (-1.9AX)
                                             + (1.9*TM) + (3.2*
                                             IN) + (-0.8*SC) + 17.37
   Investigative (n = 230)           10.19  (-1.9*EX) + (1.4*IN) +
                                             (-1.2*AX) + 32.36
   Artistic (n = 230)                 9.86  (-3.3*TM) + 40.20
   Social (n = 229)                   7.66  (1.4*EX) + (-1.7*TM)
                                             + (0.5*SC) + 33.14
   Enterprising (n = 230)             8.18  (0.6*TM) + (2.2*IN) +
   Conventional (n = 229)            10.61  (0.7*TM) + (0.9*SC) +
                                             + 13.71

Primary factor score equations (**)
   Realistic (n = 230)                8.65  (-3.0*1) + (-1.1*A) +
                                             (1.7*Q1) + 33.66
   Investigative (n = 229)            9.55  (-1.8*A) + (-0.4*1) +
                                             (1.4*B) + (-0.7*Q4)
                                             + (1.2*Q1) + 23.64
   Artistic (n = 230)                 9.84  (2.1*1) + (1.2*M) +
                                             (1.4*Q1) - 3.92
   Social (n = 230)                   7.36  (2.0*A) + (0.8*H) +
                                             (1.0*Q1) + 13.85
   Enterprising (n = 230)             8.06  (1.0*A) + (1.6*E) +
                                             (0.55*H) + (-0.8*1)
                                             + (0.7*N) + 9.87
   Conventional (n = 222)            10.70  (-1.0*M) + 27.63

Note. See Table 1

Note. SEE = Standard Error of the Estimate.

(a)A-[R.sup.2] is the adjusted [R.sup.2] for the equation with the
multiple R in parentheses.

(b)Letters represent scale names (Conn & Rieke, 1994).

(**)p < .01.
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Author:Page, Betsy J.
Publication:Career Development Quarterly
Article Type:Statistical Data Included
Geographic Code:1USA
Date:Dec 1, 2001
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