For this example I have used blocks from 1338 samples taken from 773 Scotch pine trees in southeast Finland. (PISY = Pinus sylvestris. Samples are available at the ITRDB in several files by Meriläinen, Lindholm, Timonen and others).
As the reference (the chronology) I have used ITRDB:mt112 (PIFL = Pinus flexilis, AD 470-1998 i.e 1528 years, Montana, USA by King, Waggoner & Graumlich).

In order to avoid blocks containing zero-rings and shorter overlap than stated, the minimum overlap should be set to the same value as the block length. In CDendro you also have to uncheck all collection members which are shorter than the specified block length. In order to get many blocks for testing you may prefer quite a short distance between the blocks. Though, this will give a risk that tested blocks would look rather similar, and the same false hit will possibly be reported several times. So, as a middle course, I prefer to set the block distance value at half of the block length value.

Helping context. In practical dendrochronological work you often have several samples from the same context, which can support each other for a certain crossdating towards a reference, even if they taken one by one may give a little too low crossdating values.

When zero rings needed. When a zero ring is needed to make a sample crossdate properly, you have to be very suspicious when all rings look normal. With e.g. pine samples it sometimes happen that rings are missing in parts of the ring-circuit although the surrounding rings look quite normal. If a crosscut is available, then such incomplete rings can often be identified. When working with cores only, it is often impossible to see where there is a missing ring. So when inserting a ring to make good correlation values, it is necessary to remember that such correlation values, to some extent are somewhat invented and have to be handled with great suspicion. To be sure about the correctness of inserting a ring, the blocks at one or each side of the inserted ring (or rings) should itself have values good enough to justify its dating.

The following test is therefore relevant only if compared with “clean” samples without any inserted rings (or excluded false rings) and without “helping context”.

80 years long blocks, starting at every 40 year gives some 3800 blocks to be tested with an overlap of 80 years. The statistics here are given for all the four standard normalization methods in CDendro, i.e.Proportion of last two years growth, Besancon index E, Hollstein and Baillie/Pilcher.

The analysis shows that the “safety level” has to be set a little bit higher for Baillie/Pilcher and Hollstein normalization than for “Proportion of last two years growth”. Also the "safety level" has to be set a little bit higher for "Proportion of last two years growth" than for the "Besancon index E" method.

Note: The lowest required TTest-value grows with shorter block lengths!

Number of best false matches grouped by TTEST value and normalization method Block length: 80 years Normalization method: Besancon (no logarithm) Prop 2 yrs Hollstein Baillie/Pilcher False TTest >= 7.0: 0/3751 (0%) 0/3812 (0%) 0/3812 (0%) 0/3777 (0%) False TTest >= 6.5: 0/3751 (0%) 1/3812 (0.03%) 4/3812 (0.1%) 5/3777 (0.1%) False TTest >= 6.0: 1/3751 (0.03%) 4/3812 (0.1%) 7/3812 (0.2%) 13/3777 (0.3%) False TTest >= 5.5: 16/3751 (0.4%) 17/3812 (0.4%) 27/3812 (0.7%) 44/3777 (1.2%)   False TTest >= 5.0: 61/3751 (1.6%) 86/3812 (2.3%) 99/3812 (2.6%) 150/3777 (4.0%) False TTest >= 4.5: 263/3751 (7%) 328/3812 (9%) 371/3812 (10%) 585/3777 (15%) Block length: 120 years Normalization method: Besancon (no logarithm) Prop 2 yrs Hollstein Baillie/Pilcher False TTest >= 7.0: 0/1799 (0%) 0/1835 (0%) 0/1835 (0%) 0/1816 (0%) False TTest >= 6.5: 0/1799 (0%) 0/1835 (0%) 0/1835 (0%) 1/1816 (0.1%) False TTest >= 6.0: 0/1799 (0%) 2/1835 (0.1%) 5/1835 (0.3%) 4/1816 (0.2%) False TTest >= 5.5: 2/1799 (0.1%) 4/1835 (0.2%) 8/1835 (0.4%) 12/1816 (0.7%)   False TTest >= 5.0: 14/1799 (0.8%) 25/1835 (1.4%) 32/1835 (1.7%) 61/1816 (3%) False TTest >= 4.5: 95/1799 (5%) 114/1835 (6%) 131/1835 (7%) 209/1816 (12%)

How to read the tables: See the first table above: When testing some 3800 blocks of 80 years length towards an uncorrelated reference of 1528 years, no block had a best match above TTest=7.0 The rightmost cell of the "TTest>=5.0 line" tells that when using Baillie/Pilcher normalization, as many as 4% of the blocks had a best TTest >= 5.0, which all were erroneous matches, i.e. "False TTest". The block length has a strong impact on the risk level of false high TTest-values:

Number of best false matches grouped by TTEST value and block length                                                                                                                        Normalization method: Proportion of last 2 years growth (Prop 2 yrs) Block length: 50 years 60 years 80 years 120 years False TTest >=7.0: 1/6994 (0.01%) 0/5568 (0%) 0/3812 (0%) 0/1835 (0%) False TTest >=6.5: 5/6994 (0.07%) 3/5568 (0.05%) 1/3812 (0.03%) 0/1835 (0%) False TTest >=6.0: 23/6994 (0.3%) 10/5568 (0.2%) 4/3812 (0.1%) 2/1835 (0.1%) False TTest >=5.5: 76/6994 (1.1%) 37/5568 (0.7%) 17/3812 (0.4%) 4/1835 (0.2%) False TTest >=5.0: 273/6994 (3.9%) 151/5568 (2.7%) 86/3812 (2.3%) 25/1835 (1.4%) False TTest >=4.5: 948/6994 (14%) 639/5568 (11%) 328/3812 (9%) 114/1835 (6%)                                                                                                                        Normalization method: Besancon index E - No logarithm Block length: 50 years 60 years 80 years 120 years False TTest >=7.0: 1/6846 (0.01%) 1/5481 (0.02%) 0/3751 (0%) 0/1799 (0%) False TTest >=6.5: 1/6846 (0.01%) 2/5481 (0.02%) 0/3751 (0%) 0/1799 (0%) False TTest >=6.0: 8/6846 (0.1%) 6/5481 (0.1%) 1/3751 (0.03%) 0/1799 (0%) False TTest >=5.5: 41/6846 (0.6%) 18/5481 (0.3%) 16/3751 (0.4%) 2/1799 (0.1%) False TTest >=5.0: 193/6846 (2.8%) 100/5481 (1.8%) 61/3751 (1.6%) 14/1799 (0.8%) False TTest >=4.5: 728/6846 (11%) 489/5481 (9%) 263/3751 (7%) 95/1799 (5%)

Note: The Besancon algorithm has two optional logarithmic modes, standard eLog and the "Besancon logarithm" defined as normV = if (normV>0) then log(normV) else -log(-normV) The numbers of erroneous matches found in the "Besancon (no logarithm)" case with block length 80 were 0/0/1/16/61/263 (see the first table above). For the eLog variant the numbers are: 0/0/2/19/71/280 For the BesLog variant the numbers are: 0/0/3/13/54/273 I.e. about the same result with all three variants. With CDendro the normalized mean value reference - created from a collection - can be made in two different ways: either as a mean value curve from all the normalized ring width curves of the collection or as a normalized curve made from the mean value ring width curve (a .wid-file) created from all the ring width curves of the collection. Tests have been run with both types of reference curves. No significant differences have been found between the two methods for this case where we are only looking for false matchings. The tables above show the numbers from the case with a reference created out of mean values of normalized collection members, i.e. that reference you get when you press the "Create mean value sample" button in the CDendro collection. Files used for the tests above

Torbjörn Axelson (2008-08-26)
Revised by Lars-Åke Larsson 2009-03-15 (Besancon related data added.)