Assessing physical activity in inpatient rehabilitation—sensor-based validation of the PAIR

Increased physical activity is positively associated with better health in community-dwelling older persons. It is unclear whether physical activity also influences success of inpatient rehabilitation. For the assessment of physical activity in inpatient rehabilitation the Physical Activity in Inpatient Rehabilitation Assessment (PAIR), a short questionnaire based on five questions, was developed and preliminary validated. In this study, the PAIR was validated against a sensor-based physical activity measurement. Seventy functionally impaired and cognitively mostly intact patients of a German geriatric inpatient rehabilitation clinic who had undergone hip surgery (n?=?62 women, median age?=?83 years) participated. Physical activity was measured using the PAIR and a sensor-based activity monitor (Physilog ®; BioAGM, CH). Assessments were conducted at admission (T1) and 2 weeks later (T2) during the rehabilitation process. To assess concurrent and predictive validity, Spearman correlations and linear regression models were calculated using sensor-based walking activity and uptime activity (walking and standing time) as dependent variables. Criterion-related concurrent validity using physical activity sensors was weak to moderate. Correlations were slightly higher at T2 (r?=?0.45-0.53) than at T1 (r?=?0.44-0.46). The objectively measured variance of physical activity, explained by the PAIR, ranged from 25 to 43 %. PAIR activity scores and sensor-based walking or total activity increased in a dose-dependent manner, confirming the scoring system of the PAIR. The application time was usually less than 2 min. The validity of the PAIR is weak to moderate when compared to a sensor-based activity monitor and comparable to existing physical activity assessments for community-dwelling older adults.     

Accelerometry analysis of physical activity and sedentary behavior in older adults: a systematic review and data analysis

Accelerometers objectively monitor physical activity and sedentary patterns and are increasingly used in the research setting. It is important to maintain consistency in data analysis and reporting, therefore, we: (1) systematically identified studies using accelerometry (ActiGraph, Pensacola, FL, USA) to measure moderate-to-vigorous physical activity (MVPA) and sedentary time in older adults, and (2) based on the review findings, we used different cut-points obtained to analyze accelerometry data from a sample of community-dwelling older women. We identified 59 articles with cut-points ranging between 574 and 3,250 counts/min for MVPA and 50 and 500 counts/min for sedentary time. Using these cut-points and data from women (mean age, 70 years), the median MVPA minutes per day ranged between 4 and 80 min while percentage of sedentary time per day ranged between 62 % and 86 %. These data highlight (1) the importance of reporting detailed information on the analysis assumptions and (2) that results can differ greatly depending on analysis parameters.     

Looking for homogeneous groups of respondents and nonrespondents using latent class analysis

Concerns about decreasing response rates have led to many nonresponse studies. Unfortunately, usually only a limited amount of data is available on nonrespondents. Linking administrative data makes information available on all the sampled units including nonrespondents. Statistics Netherlands has constructed a database in which several administrative records and several surveys are connected. In this explorative study we use this dataset to look for homogenous groups of respondents and nonrespondents in survey research using latent class cluster analysis. Latent class techniques can provide insight into the problem of selective nonresponse and currently under-represented societal groups. We identify four different latent classes in a recent Dutch survey and replicate the findings for the same survey conducted 4 years later. Two of the types of sampled units have above-average response rates and the other two have below-average response rates. We also evaluate various latent class models with other response outcomes to gain insight into the contact and cooperation process.     

High precision implementation of Steck's recursion method for use in goodness-of-fit tests

Classical continuous goodness-of-fit (GOF) testing is employed for examining whether the data come from an assumed parametric model. In many cases, GOF tests assume a uniform null distribution and examine extreme values of the order statistics of the samples. Many of these statistics can be expressed by a function of the order statistics and the p-values amount to a joint probability statement based on the uniform order statistics. In this paper, we utilize Steck''s recursion method and propose two high precision computing algorithms to compute the p-values for these GOF statistics. The numerical difficulties in implementing Steck''s method are discussed and compared with solutions provided in high precision libraries.     

MODELING THE ALLOCATION OF GRADUATE STUDENT FINANCIAL AID

Universities have always competed with one another for the relatively small number of highly qualified students interested in graduate education. This competition has been intensified recently by adverse demographic trends. This paper is concerned with the use of financial aid awards as a means of competition and with allocation of awards so that enrollments are maximized while satisfying academic standards and budget constraints. It also considers the randomness of actual aid disbursements and develops models of incremental aid allocation that increase enrollments but are within tolerance levels for budget overruns.     

SELECTING PARAMETERS FOR SHORT-TERM FORECASTING TECHNIQUES

The objective of this paper is to discover which of three forecasting modes used to select parameters for four short-term forecasting techniques minimizes errors. The study also examines whether the amount of historical data used to find parameters contributes to forecasting success. The results show the traditional one-ahead search routine works well in some, but not all, forecasting situations. Also, forecasting errors appear to decline when more historical data are included in the parameter search.     

VALIDATION OF EXPERT SYSTEMS- WITH APPLICATIONS TO AUDITING AND ACCOUNTING EXPERT SYSTEMS*

This paper proposes a set of definitions for the concepts “validation” and “assessment” applied to expert systems (ESs). It develops a framework for this validation and demonstrates the framework on existing accounting and auditing ESs to elicit some of the research issues involved in ES validation. Validation is critical to the design and implementation of decision-making ESs. In a setting where objectivity is sought and variance is avoided, validation ascertains what a system knows, knows incorrectly, or does not know. Validation ascertains the system's level of expertise and investigates the theoretical basis on which the system is based. It evaluates the reliability of decisions made by the system. The validation framework developed in this paper is research methods. It is designed to reflect the unique aspects of ESs (in contrast to other types of computer programs) and can be used by ES developers as a basis from which to perform validation and by researchers as a framework to elicit research issues in validation.