title: What scanner-panel data tell us about advertising

authors: Koslow, Scott

subjects: advertising

abstract: There have been some news releases claiming that Professor Henle in Germany has found the chemical identity of UMF, and that in future chemical analysis will be used instead of assays of antibacterial activity to indicate the level of UMF in manuka honey. Both of these claims are misleading. Because the level of active substance in manuka honey is an unreliable indication of the level of antibacterial activity and can be very misleading, it is hard to see any commercial advantage for it to be used to indicate antibacterial activity other than if someone wanted to fool the consumer into thinking that the higher numbers are giving them a level of antibacterial activity that is far higher than they are really getting.

text: What scanner-panel data tell us about advertising There have been some news releases claiming that Professor Henle in Germany has found the chemical identity of UMF, and that in future chemical analysis will be used instead of assays of antibacterial activity to indicate the level of UMF in manuka honey. Both of these claims are misleading. Because the level of active substance in manuka honey is an unreliable indication of the level of antibacterial activity and can be very misleading, it is hard to see any commercial advantage for it to be used to indicate antibacterial activity other than if someone wanted to fool the consumer into thinking that the higher numbers are giving them a level of antibacterial activity that is far higher than they are really getting.

year: 2011

title: Comparison of spatial prediction techniques for developing Pinus radiata productivity surfaces across New Zealand

authors: Palmer, David John

subjects: plantation forestry

abstract: Spatial interpolation is frequently used to predict values across a landscape enabling the spatial variation and patterns of a property to be quantified. Inverse distance weighting (IDW), ordinary kriging (OK), regression kriging (RK), and partial least squares (PLS) regression are interpolation techniques typically used where the region of interest's spatial extent is relatively small and observations are numerous and regularly spaced. In the current era of data ‘mining’ and utilisation of sparse data, the above criteria are not always fully met, increasing model uncertainties. Furthermore, regression modelling and kriging techniques require good judgement, experience, and expertise by the practitioner compared with IDW with its more rudimentary approach. In this study we compared spatial predictions derived from IDW, PLS, RK, and OK for Pinus radiata volume mean annual increment (referred to as 300 Index) and mean top height at age twenty (referred to as Site Index) across New Zealand using cross-validation techniques. Validation statistics (RMSE, ME, and R2) show that RK, OK, and IDW provided predictions that were less biased and of greater accuracy than PLS predictions. Standard deviation of rank (SDR) and mean rank (MR) validation statistics showed similar results with OK the most consistent (SDR) predictor, whereas RK had the lowest mean rank (MR), closely followed by IDW. However, the mean performance rankings for validation observations classified according to their distance to the nearest model data point indicate that although PLS provided the poorest predictions at relatively close separation distances (<2 km), in the medium range ( 4–8 km) performance was of similar ranking to that of the other techniques, and at greater separation distances PLS outperformed the other techniques. Maps illustrating the spatial variation of P. radiata forest productivity are provided.

text: Comparison of spatial prediction techniques for developing Pinus radiata productivity surfaces across New Zealand Spatial interpolation is frequently used to predict values across a landscape enabling the spatial variation and patterns of a property to be quantified. Inverse distance weighting (IDW), ordinary kriging (OK), regression kriging (RK), and partial least squares (PLS) regression are interpolation techniques typically used where the region of interest's spatial extent is relatively small and observations are numerous and regularly spaced. In the current era of data ‘mining’ and utilisation of sparse data, the above criteria are not always fully met, increasing model uncertainties. Furthermore, regression modelling and kriging techniques require good judgement, experience, and expertise by the practitioner compared with IDW with its more rudimentary approach. In this study we compared spatial predictions derived from IDW, PLS, RK, and OK for Pinus radiata volume mean annual increment (referred to as 300 Index) and mean top height at age twenty (referred to as Site Index) across New Zealand using cross-validation techniques. Validation statistics (RMSE, ME, and R2) show that RK, OK, and IDW provided predictions that were less biased and of greater accuracy than PLS predictions. Standard deviation of rank (SDR) and mean rank (MR) validation statistics showed similar results with OK the most consistent (SDR) predictor, whereas RK had the lowest mean rank (MR), closely followed by IDW. However, the mean performance rankings for validation observations classified according to their distance to the nearest model data point indicate that although PLS provided the poorest predictions at relatively close separation distances (<2 km), in the medium range ( 4–8 km) performance was of similar ranking to that of the other techniques, and at greater separation distances PLS outperformed the other techniques. Maps illustrating the spatial variation of P. radiata forest productivity are provided.

year: 2009

title: Tiakina te Pā Harakeke: Māori Childrearing practices within a context of whānau ora.

authors: Pihama, Leonie

abstract: ‘Tiakina Te Pā Harakeke’ was developed to support the investigation and identification of  Kaupapa Māori	approaches to Māori childrearing and parenting. The project investigates how we can draw upon such frameworks to support intervention in the area of child abuse and child neglect within our whānau. ‘Tiakina Te Pā Harakeke’ is a research project that brings to the fore	the successful values and practices of childrearing that have been held within whānau, hapū and iwi for many generations. It is an exploration and sharing of knowledge that supported the belief held by our tūpuna that our tamariki and mokopuna are treasured parts of whānau, hapū and iwi, as is expressed in the saying	‘he taonga te mokopuna’.

text: Tiakina te Pā Harakeke: Māori Childrearing practices within a context of whānau ora. ‘Tiakina Te Pā Harakeke’ was developed to support the investigation and identification of  Kaupapa Māori	approaches to Māori childrearing and parenting. The project investigates how we can draw upon such frameworks to support intervention in the area of child abuse and child neglect within our whānau. ‘Tiakina Te Pā Harakeke’ is a research project that brings to the fore	the successful values and practices of childrearing that have been held within whānau, hapū and iwi for many generations. It is an exploration and sharing of knowledge that supported the belief held by our tūpuna that our tamariki and mokopuna are treasured parts of whānau, hapū and iwi, as is expressed in the saying	‘he taonga te mokopuna’.

year: 2014