How to Grow Strawberries in the Home Garden

PDF pages: 1

Bramble Fruit Culture

PDF pages: 1

Grape Growing

PDF pages: 2

Measurement Invariance and Response Bias: A Stochastic Frontier Approach

The goals of the present paper were to assess measurement invariance using a common econometric method and to illustrate the approach with self-reported measures of parenting behaviors before and after a family intervention. Most recent literature on measurement invariance (MI) in psychological research 1) explores the use of structural equation modeling (SEM) and confirmatory factor analysis to identify measurement invariance, and 2) tests for measurement invariance across groups rather than across time. We use method, Stochastic Frontier Estimation, or SFE, to identify response bias and covariates of response bias both across individuals at a single point in time and across two measurement occasions (before and after participation in a family intervention). We examined the effects of participant demographics (N = 1437) on response bias; gender and race/ethnicity were related to magnitude of bias and to changes in bias across time, and bias was lower at posttest than at pretest. We discuss analytic advantages and disadvantages of SFE relative to SEM approaches and note that the technique may be particularly useful in addressing the problem of “response shift bias” or “recalibration” in program evaluation -- that is, a shift in metric from before to after an intervention which is caused by the intervention itself and may lead to underestimates of program effects.Measurement invariance, measurement equivalence, response bias, response-shift bias, stochastic frontier analysis

Training and Pruning Fruit Trees

PDF pages: 2

Detecting Selection Bias in Community Disseminations of Universal Family-Based Prevention Programs

The goals of the present study were to demonstrate a method for examining selection bias in large-scale implementations of community-based family skills programs, and to explore the nature of selection bias in one such implementation. We used evaluation data from a statewide dissemination of a popular substance abuse prevention program (N programs = 42; N youth = 294). The program’s evaluation measures were designed to match publicly available data on risk and protective factor scales collected in the state’s schools, which enabled us to construct a comparison sample of non-participants (N = 20,608). We then examined the risk status of adolescents in both groups to determine whether risk and protective factor scores were related to the probability of program participation. Participation was predicted by both demographics and risk and protective factor scores. Among families with younger adolescents, program attendance was associated with lower risk; among families with older adolescents, participation was associated with both higher risk (on parental management skills) and lower risk (on substance use). Selection effects must be identified and corrected for in order to calculate valid estimates of program benefits, but in community-based disseminations, the necessary supplemental comparison sample is difficult to obtain. The evaluation design and analytic approach described here can be used in program evaluations of real-world, “bottom-up” dissemination efforts to identify who attends a program, which in turn can help to inform recruitment strategies, to pinpoint possible selection influences on measured program outcomes, and to refine estimates of program costs and benefits.repeated auction; selectivity; prevention program; community-based implementation; program evaluation

Estimating treatment effectiveness with sample selection

We consider a situation where treatment outcome is observed after two stages of selection; first of participation into the treatment, then in completion of the treatment. Estimates were obtained using two methods. First, three different binary response selection models were estimated sequentially in multiple steps. Second, all three equations were estimated jointly. All methods produce similar parameter estimates. We find evidence of selection effects from completion to outcome that could bias parameter estimates of the outcome equation, but not from participation to outcome, indicating that correcting only for participation may be insufficient to avoid biased estimates in the outcome equation.selection bias, trivariate probit, bivariate probit, treatment effects

75th Anniversary American Abstract Artists Print Portfolio (Exhibition Catalogue)

Catalogue documenting the 75th Anniversary digital print portfolio of the American Abstract Artists. Participating artists were: Alice Adams, Siri Berg, Emily Berger, Susan Bonfils, Power Boothe, Henry Brown, Kenneth Bushnell, James O. Clark, Gabriele Evertz, John Goodyear, Gail Gregg, James Gross, Lynne Harlow, Mara Held, Daniel G. Hill, Gilbert Hsaio, Phillis Ideal, Julian Jackson, James Juszczyk, Cecily Kahn, Steve Karlik, Marthe Keller, Irene Lawrence, Jane Logemann, Vincent Longo, David Mackenzie, Stephen Maine, Katinka Mann, Nancy Manter, Creighton Michael, Manfred Mohr, Hiroshi Murata, John Phillips, Lucio Pozzi, Leo Rabkin, Ce Roser, David Row, Edward Shalala, Robert Storr, Robert Swain, Clover Vail, Vera Vasek, Don Voisine,Stephen Westfall, Jeanne Wilkinson, Mark Williams, Thornton Willis, and Nola Zirin